Ted’s Numbers

M. Norton Wise, Mary S. Morgan, Emmanuel Didier, Lorraine Daston and Soraya de Chadarevian

Rounded Globe


  1. Preface
  3. Margo Anderson ENCOUNTERING TED
  5. Jean-Pierre Beaud & Jean-Guy Prévost TRUST IN PORTER
  7. Dan Bouk COUNT ME
  10. Karine Chemla TRUST IN Π
  11. Roser Cussó THE MYSTERY LIVES ON
  12. Lorraine Daston THE VOICE OF TED
  13. Soraya de Chadarevian MORE THAN JUST ABOUT NUMBERS
  14. Emmanuel Didier TED’S PERSPECTIVES
  15. Wendy Espeland FACTS and ODE TO TED
  16. Gerd Gigerenzer ALL IN THE NUMBERS
  18. Morgane Labbé AT THE BORDER
  20. Martha Lampland TED PORTER
  25. Martine Mespoulet SOLVING A RIDDLE
  28. Christine von Oertzen PAULINE’S PETITION
  29. Jahnavi Phalkey ALL BECAUSE OF TED!
  36. Jessica Wang TRUST IN TED


How many scholars over the course of their careers come to be known as founders of a new field of study? Theodore M. Porter is such a person. The field is Historical and Social Studies of Quantification. It crosses over from Ted’s own beginnings in history of science to people working in sociology, economics, accounting, biological evolution, and philosophy. Even more unusually, perhaps, Ted is not only admired but loved by all of those people who have found their own inspiration for work in the field they were creating with him, partly from simply reading his publications but especially from direct interaction with him. Even on the printed page, Ted’s wit and deep humanity impressed his readers, as well as his brilliance and learning. This volume collects some of their personal memories of those interactions. It is an appreciation of his personal qualities as a scholar and a friend. It marks the occasion of his retirement after many years at UCLA.

Although these brief reflections on Ted and his numbers do not aim at an academic exposition of his intellectual work, that work is nevertheless a constant reference point. A full CV would list six books, over a hundred articles, many, many reviews and comments, and a constant presence at workshops and conferences throughout Europe and North America. But everyone would agree that Ted’s position as founder of a field rests on four major books, each of which is wholly original and constitutes a pillar of Quantification Studies. Because our authors typically refer to these works only implicitly or in short form, we give them here with full citation.

The Rise of Statistical Thinking, 1820-1900 (Princeton U. Pr., 1986) appeared when no synthetic history of statistics yet existed (although Stephen Stigler’s important book appeared in the same year). But Ted’s volume was not simply a history of statistics as mathematics; it was a history of statistical thinking, and that made all the difference. He showed that statistical thinking throughout the nineteenth century and beyond was shaped by analogies drawn from social, political, and economic concerns. That theme has run through his work ever since.

Trust in Numbers: The Pursuit of Objectivity in Science and Public Life is Ted’s most famous book. In it he proposed the thoroughly counterintuitive thesis that the ubiquitous appeal to numbers to establish policy goals in modern democracies derives not from the professional strength of their state bureaucracies but precisely from their weakness. The numbers, established by fixed rules and methods for measurement, provide objectivity in the sense of non-subjectivity, non-dependence on the personal judgement of any individual.

Karl Pearson: The Scientific Life in a Statistical Age (Princeton Univ. Pr., 1995) draws on a massive archive to narrate the life of the founder of modern mathematical statistics. But the brilliant innovator emerges as a complex personality, one as deeply rooted in disparate social developments as was statistics itself. As Pearson himself put it, “It is impossible to understand a man’s work unless you understand . . . the state of affairs social and political of his own age.”

Genetics in the Madhouse: The Unknown History of Human Heredity (Princeton Univ. Pr., 2018) tells us in its title that we are going to be surprised, that the history of heredity is not the history of the gene. Genetics has been critically important in the twentieth century of course, but its story emerged from a much longer one on heredity as the supposed basis of mental illness and on the attempt to quantify its effects in statistical tables. This was the work of asylum directors and doctors, who in different countries and in different ways sought to rationalize their practices through quantification. Ted’s story is one of state institutions, social policies, and governance. He has taught us that this scenario has been typical in the history of statistical analysis.

We thank Ted Porter for his continually enlightening intellect and for his unfailing kindness and humor.

Simon J. Cook of Rounded Globe has kindly guided us through the process of making an ebook.

Aurélie Slonina has created our cover design. We thank her warmly.


In 2007, Ted asked me to introduce him for his ‘Distinguished Lecture’ at that year’s History of Science Society meeting in Arlington, Virginia. I take the liberty of reproducing that introduction here (lightly edited for clarity) because it expresses how I felt then—and still do.

This is an awkward introduction for me to make, but not for the reasons you might think. It’s obviously not because I’m going to say something critical about Ted’s work. The occasion alone makes it evident that I’m going to say something complimentary. But that is what makes this so awkward. I can’t joke around. I have to tell you honestly how I feel about his work. And to be honest, I have to say that I love it. The reason that this is awkward to say is not because academics are supposed to be critics all the time and pick apart everything we read. No, lots of us admire one another’s work, and there is no shame in admitting this publicly and often.

The problem is that I didn’t say that I “admired” Ted’s work. I said that I “loved” it. Which points to how oddly constrained we are in the sort of language we’re allowed to use in the polite society of academia. Sure, we are expected to pile up stacks of positive adjectives in our letters of recommendation, in our referee reports, and in our evaluations for tenure and promotion. But we remain oddly dispassionate about our superlatives. All of our adjectives are so—dare I say it?—‘objective.’ We use words like ‘excellent’ and ‘superb’ and even ‘superlative,’ as if we were evaluating academic work on a monotonic, single-factor sliding scale of superlativeness. Whereas if I were to speak truthfully and from the heart—and not as the sort of introducer who is expected to explain how Ted Porter’s work is analytically insightful and important to the development of the field—then I would say that I love his work because it mattered to me, subjectively.

I first read Ted’s work while I was trying to transform my own shambolic 800-page dissertation into a book, and his work helped me solve the central intellectual puzzle I had been wrestling with—even as it gave me scope to think for myself. I think we should honor this sort of intellectual gift more than any other; a style of thinking that gives others scope to think for themselves. I’ve always loved that in Ted Porter’s books and articles. Trust in Numbers came first for me, then The Rise of Statistical Thinking, and later, Karl Pearson; plus his contributions to the Bielefeld collective.

Almost all of Ted’s work is organized around a singular subject—the history of statistics—but each of his books follows a different set of frazzled experts as they wrangle over how to assemble their peculiar sector of the infrastructure of modernity. What these books taught me was that historians could reverse-engineer that messy process. Ted is famously the man who can make the history of statistics funny. And much of his ironic humor, I now think, comes from the disjuncture between that messy process and the final product. It’s an eye-opening lesson.

But now I’m drifting into appreciation, which is exactly what I promised I would avoid.

So let me say instead that what mattered to me—both then and now—was that Ted’s work showed me that there was a way to write the history of science that made me enjoy writing the history of science. Imagine that: the history of science as a joyous kind of work! And it was that, more than anything else, which made me love it.

And then, shortly before my own book came out, Ted and I met in person and we became friends, and this made me like academia too. (Note that I said “like” academia, not “love” academia, but then, I also promised I’d be truthful.)

Which is why I am delighted to introduce Ted Porter, who is going to explain ‘How Science Became Technical.’

Northwestern University


My memory is hazy here, but I know I was reading and learning from Ted’s work some 40 years ago as I started venturing into the history of statistics and state-based data systems.

My initial interest was trying to figure out why historians and folks in general didn’t recognize how important the census was to American politics, to the cultural understanding of America, why folks treated it as ‘objective’—like an old shoe that was sort of just there, truth, easy to see.

I’d come at my interest in the census from a very practical place. I was using a lot of census data for a quantitative dissertation in urban and labor history, analyzing occupational change over time, and I kept being frustrated by the inconsistencies I found in the data I was retrieving. Why did the census reports in some years have these kinds of tables, and in other years, they didn’t. Why did some time series break and others didn’t? Like a good historian, I went to the old journals, and to the archives, the National Archives in particular, to look at the historical records of the census takers. What did they think they were doing? What did they mean by various terms, classifications, controversies, at the time the data were published.

I opened a much bigger Pandora’s box than I expected, managed to get enough insight to do the dissertation, publish it in a really obscure book series, and then turned my attention to the bigger questions that I now thought were embedded in the history of state-based quantitative data systems.

So a new venture into the history of science and technology to see who else was working on these questions. And I found Ted’s Rise of Statistical Thinking. Not his book alone, of course, but what Ted’s work did for me was introduce me to the European scholarly world and the history of science world on these matters. So, that book and all his later work have anchored me ever since, while I ventured in a somewhat different direction, namely into an ‘American case,’ the ‘politics of numbers,’ historical analysis of the policies surrounding official statistical data collection and use, and the really complicated intellectual world of statisticians, computer scientists, politicians, social scientists, humanists, and the public who determine these things.

I last was able to spend some time with Ted at the 2017, EU organized, Power from Statistics Conference in Brussels. We were staying in the same neighborhood near the conference, and were able to chat, share interests, generally catch up at the conference and at dinners that week. Genetics in the Madhouse wasn’t out yet, but I learned about the book, his European research, again, matters that I would not have encountered in my ‘American’ scholarly world.

It’s been a long scholarly conversation, threads picked up years, if not decades apart. And it should continue. Happy Retirement, Ted!

University of Wisconsin - Milwaukee


For the historians of tomorrow, a book could appear as the cornerstone of the new science that studies the growing role of the quantification of the world: the work of the historian Ted Porter, published in 1995, Trust in Numbers. The Pursuit of Objectivity in Science and Public Life (TN).

While academic endeavors to promote a sociology of quantification are multiplying, in bringing together under the same prism quantifications of very different natures, sometimes physico-chemical, sometimes statistical, sometimes accounting or even financial, TN constituted a vanguard. In this first respect, the work had an important impact, in particular in France where Alain Desrosières, who was to quickly forge solid links with Porter, had just published the reference book of the French school of sociology of statistics: The Politics of Large Numbers.

Porter had participated in the famous Bielefeld seminar which led to the publication of The Probabilistic Revolution (1987), well known to those who are engaged in the development of the history and sociology of statistical science and statistical data. He himself had taken the material from it for his book The Rise of Statistical Thinking, 1820-1900. And in this dynamic, he had first considered looking into the mathematization of economics.

But passionate about science ‘in society’ and considering the economy too often cut off from the field of public action, he had finally decided to take an interest in the technologies mobilized by managers, these hybrids of science and politics that he refers to as ‘trust technologies.’

His idea is that quantification is as much the work of science as that of the political contexts in which public powers or companies impose themselves on the expert or managerial professions, science being ultimately often reluctant to quantify and more fond of the establishment of laws and theoretical models: “Quantification is a social technology (…) closely allied to the practical world of commerce and administration” (TN).

His research on statistical science and its various associated quantifications had offered him a first field of investigation on these technologies. His interest in economic history suggested a second: financial quantifications. TN thus offered an unprecedented cross-sectional look at these two forms of quantification built and mobilized to establish trust conducive to good governance.

Looking at statistics and accounting in a transversal way was Porter’s epistemological coup de force which marked the field of HSS research. He upset the lines, in France in particular where Desrosières, at the same time as he imposed on his students the reading of TN, reconsidered the direction of his research: he, the administrator of INSEE who had become a sociologist of statistics, extended to accounting his perspective and gradually saw it as a “historical sociology of quantification.” He first formulated it on the occasion of a symposium organized in 2002 with Eve Chiapello and in which Ted Porter was one of the two keynote speakers, alongside Peter Miller. He finally made it the title of a book (2008). This influence of TN on the French school is the reason for its judicious translation by Les Belles Lettres.

When the French edition of TN was published in 2017, the stakes in the academic field were doubly reversed. For all the heirs of The Probabilistic Revolution (and others), it had become obvious that statistics and accounting should be subject to the same sociological perspective. TN had won its first victory: unifying the sociological study of the numbers that build collective trust in science and public life.

But between 1995 and 2017, a second reversal occurred, within the very field of financial quantifications, directly linked to a notion that had emerged in the meantime: ‘financialization.’ While financial accounting has been established since its genesis (from the 14th century in Europe) ‘in historical costs,’ international standardization, driven in particular by the European Union (which adopted IFRS in 2002) has opted for new accounting ‘at fair value.’ This requires considering that behind the banner of numbers (financial accounting in particular), we have to design a sociology of their various families, associated with rival agents and interests. It is precisely the second track that TN proposed, in a less visible way (i.e. vice versa).

In TN, Porter reviewed various varieties of financial quantification: classical accounting, contemporary with the first capitalist economies, the cost/benefit calculations associated with public works or the probabilistic calculations of actuaries, both enjoying success in the nineteenth century, the first rather on French and American soil, the latter first on English. And for each type, Porter recalled the political contexts of their development as well as the pioneering works on which he based his enterprise: those of Lorraine Daston on the first mobilizations of probabilities in the conduct of societies, those of A. Loft or T. Johnson and R. Kaplan on the rise of managerial accounting in the twentieth century, by T. Alborn, R. Parker or Mike Power on the probabilistic shift in financial accounting, or even by F. Etner and A. Picon concerning the economic calculation of French engineers, and M. Keller about the US Army Corps of Engineers.

And through this fresco, Porter sketched the see-saw of financialization that no one yet called that. Exhuming a 1963 article from the Accounting Review which engaged the criticism of the positivism dominating the accounting profession clinging to the myth of ‘absolute objectivity,’ then another from a 1977 which took up the controversy to promote the new financialized techniques of accounting (based on ‘fair value’) whose use was beginning to spread among practitioners, Ted Porter shared with his friends from the LSE, Peter Miller (1991) and Mike Power (1992, 1993, 1994), the intuition that financial accounting was going to experience a revolution. He suggested to consider that behind the banner of quantifications hide rival families. Now that the financial revolution has taken place, TN can fly towards its second victory: to distinguish the new numbers of trust, those of contemporary financialized accounting which now dominate those of historical financial accounting, and thus illuminate the new distinction.

Lab EVS - ENTPE, Lyon

Jean-Pierre Beaud & Jean-Guy PrévostTRUST IN PORTER

Where to begin? Our very first encounter with Ted Porter goes back to the 1992 Social Science History Association meeting held in Chicago, at a time his first book and the output generated by his participation in the 1982-83 Bielefeld seminar had established him as a rising scholar in a rising field to the establishment of which he was playing a major part. But closer links developed when Ted generously accepted our invitation to act as keynote speaker in a 1999 conference held in Montréal on L’ère du chiffre/The Age of Numbers. As the bilingual title and the French spelling of the city indicate, language is here a political as well as an existential issue. Therefore, we both greatly appreciated Ted’s concern in this regard, his willingness to speak French more and more often and more and more fluently as he came back to Montréal (he of course could read French perfectly way before that, as can be seen from the primary sources he used in his 1986 The Rise of Statistical Thinking). And come back he did, regularly, as scientific advisor to the Centre interuniversitaire de recherche sur la science et la technologie from 2008 on, to take part in events such as the 2011 meeting held on the occasion of our institution’s bestowing of an honorary doctorate to Alain Desrosières and the 2017 conference Le chiffre et la carte, where he delivered the inaugural address, or in summer schools held in various universities.

Ted’s Francophilia meant of course that he has also been very present in France since the start of his career. Trust in Numbers—with a chapter devoted to the École Polytechnique and French engineers—was already frequently quoted and a source of inspiration for many French scholars when it was translated and published in 2017 as La confiance dans les chiffres. Beyond France, one’s path could also cross that of Ted in Italy—where Le Origini del Moderno Pensiero Statistico had appeared in 1993—or Spain, two countries where scholars devoted to the history of statistics have found in his work ideas, concepts, and insights to guide their work. The same can be said of Latin American scholars, as evidenced in the recent edited book Socio-Political Histories of Latin American Statistics. And while neither of us is familiar with the Japanese academy, we observe with amusement that both The Rise and Trust have been translated in Japanese, something that neither the French nor the Italians have done. If Adolphe Quetelet, a central figure of Ted’s first book, has been described as “the travelling salesman of statistics,” then maybe the same can be said of Ted regarding the history and sociology of statistics.

To be sure, Ted, besides being a towering figure in any group given his height, is a dominant intellectual presence in this field. A few words about his scientific contribution are thus in order, even though this is not the place to conduct any elaborate explanation or discussion. We would like to briefly underline one aspect of his work. To tentatively translate Alain Desrosières’s phrase aller au charbon, we may say that, as the coalminer who goes down the pit, Ted likes to dig deep into the archives. His most recent book offers a good example of this: we remember how startled we were the first time we heard Ted presenting on this subject, as he quoted passages from reports written by forgotten asylum directors and displayed old maps and tables about the varieties of “madness.” We wondered: Where will this lead to? Are we going to emerge from the mine? Well, we did, and the result was Genetics in the Madhouse, a book whose breadth, empirical wealth, and relevance to contemporary concerns have been hailed. There is in our view a moral quality attached to this intellectual posture, and it is humility, which is indeed, besides generosity and simplicity, an endearing trait of Ted’s personality.

Merci Ted d’avoir jeté des ponts entre les États-Unis et le reste du monde, entre l’histoire et les sciences sociales. Voyageur infatigable, conférencier toujours disponible, compagnon agréable. Le monde francophone te salue.

Université du Québec à Montréal


I will forever be grateful to the late, and fondly remembered, Alain Desrosières for introducing me to Ted Porter’s work, and then to Ted himself, sometime in the late 1990s. Alain had first directed me towards Ted’s first, seminal book on The Rise of Statistical Thinking. But soon Trust in Numbers came out, and started attracting attention from the then-thriving French history of statistics scene – a mix of historians, sociologists, and STS scholars of all stripes. The pages on the Ponts-et-Chaussées engineers clearly struck a chord, especially among the many of them who had studied or worked at an elite French engineering institution. However, the comparative approach favoured by Ted, with its wide thematic and geographical range proved puzzling to some. This was not your “traditional monograph”; it was much more interesting than that. Moving away from a conception of statistics as the powerful linchpin of an expanding, control-seeking state, the book redirected our attention to the social basis of statistical authority: the complex negotiations and arrangements on which “quantitative expertise” rested. As a Ph.D. student working on the endlessly contested attempts by the French administration to weigh up the “social cost” of alcoholism and smoking, I found it especially illuminating. The widely commented chapter on the uses of cost-benefit analysis by U.S. Army engineers firmly established that far from being the prerogative of dominant state organizations the resort to quantification sometimes amounted to a weak-to-strong strategy. Another quality of Ted’s work, in my view, was his ability to weave together the history of statistics and the coming age of objectivity. This might sound surprising, considering the manifold links between these two research fields, but he was — together with Lorraine Daston — among the few who really thought through the entanglements between quantification and mechanical, as well as disciplinary, objectivity.

I kept learning a lot from Ted in the years since then. I believe the most crucial lesson he taught us was to distrust the traditional view of scientific innovation as a process by which scientific knowledge produced at universities, scientific institutions, and (increasingly) private firms gets “applied” to public problems. From his first book onwards, Ted strove to dispel this fallacious representation of knowledge production as a one-way journey. He certainly is among those who highlighted the role of bureaucracies as sites of scientific innovation, not just “applied science” (a reductive expression often used to describe statistics) but full-fledged scientific knowledge. Not only the most prestigious “bureaux”, staffed by distinguished mandarins, but also obscure and often neglected institutions, such as the “lunatic asylums”, “schools for the feebleminded”, and prisons occupy centre-stage in his last opus so far, provocatively but aptly titled: Genetics in the Madhouse. This is an important book in many ways. Not only does it establish that shady, underfunded organizations, in the United-States, Britain, Germany, France, and other European countries, were important sites of knowledge production, even on topics such as medicine and human heredity that far exceeded the realm of the social sciences. But the book also widens the perspective of an entire research field, the history of human heredity, by highlighting the scientific relevance of lunatic asylums and related institutions, whose importance had been seen as merely political (the rising tide of mental diseases was fuelling the great fear of “degeneration”). In so doing, Ted also invited us to revisit the relationships between heredity and genetics, while shedding new light on the links between psychiatry and eugenics.

For all their differences in topic, Trust in numbers and Genetics in the Madhouse share important similarities – catchy titles being only one of them. They are wide ranging books, both from a chronological and a geographical perspective; their approach is comparative in nature; and they are both built on a thematic framework. Ted’s other major book, which interestingly came out in-between the two aforementioned, is of a strikingly different kind. Karl Pearson: The Scientific Life in a Statistical Age is neither a traditional biography, nor – strictly speaking – the history of a life-in-context, but rather a reflection on “an improbable personage”1. The book, which is of great importance to anyone with even a passing interest in the history of statistics, also has a nice reflexive twist. Ted ironically plays with the genre of biography to explore the coming of age as a scientist of the young, romantic Karl Pearson, entranced with Bildungsromane. As improbable as it might seem, the personage who – perhaps more than anyone else – has come to epitomize the rationalisation of the modern world was so enthralled with Goethe that, at the age of twenty-three, he wrote a partly-autobiographical novel transparently titled: The New Werther…

I am certainly not the most competent person to comment on Ted’s style of writing. Still, there are important features of his work which I quickly came to recognise, and appreciate very much. Meticulously researched, scholarly impeccable, sophisticated in exposition, his texts testify to a high level of intellectual engagement with the topic, not to mention a certain sense of humour – dry humour, that is. Every seasoned reader of Ted’s prose will have their own favourite quote, here is mine: “Although Trust in Numbers seems to work as a memorable title, it can mislead.”2 These are the same qualities I have seen in the man-beyond-the-author as I have become friends with him. He is a friend I am looking forward to meet again soon.

National Center for Scientific Research (CNRS), Paris


Count me among Ted’s numbers, maybe even as a ‘funny’ one.

As Ted’s work has shown, repeatedly, there is nothing simple about translating the world into numbers. “Thin description” is a thick process.

So, how did I end up as one of Ted’s numbers?

It all began with a footnote.

In 2002, I was finishing up an undergraduate degree in computational mathematics. Over the course of four years of calculus, linear algebra, and (alas) analysis, I’d determined that I enjoyed (most) mathematics, but that I longed to be closer to the beating heart of humanity. The math I encountered in the classroom seemed committed to ignoring our shared social world.

At the same time, I was reading Louis Menand’s The Metaphysical Club and trying to figure out what to do with my life. Menand devoted a chapter to the Peirce family’s use of statistical methods to expose potential foul play in an inheritance case. It was a good and rousing story, but the footnotes proved far more consequential. When I look back at them today, I see that they included a whole host of worthy books. But at the time, one title caught my eye in particular: The Rise of Statistical Thinking.

A universe of possibilities yawned before me. My heart raced.

In 2004, I decided to apply to graduate school in the history of science. But first, I bought a plane ticket to Cambridge, MA and signed myself up to attend the annual meeting of the history of science society. I attended every session I could, hungry to make sense of this new field. Today, I only remember one talk.

There, before me, (standing much taller than I had expected) was Ted Porter, who proceeded to read aloud (in his resonant baritone) a text derived from a book he had just completed. It was a moving performance, like a virtuosic aria performed by the composer. Ted set his piece—his story—in a tragic mode. His subject, Karl Pearson, distrusted specialization and he found its antidote in science. Yet, and here was the tragedy, the work he did instead ushered in an age of narrowing expertise and mechanized decision making.

Ted felt no need to reconcile or apologize for the tensions and contradictions of his subject. Ted offered up Pearson the racist and eugenicist alongside Pearson the feminist and socialist, an author of medieval passion plays and the evangelist for statistical method. Pearson worried his own full self would one day be reduced to a name on an integral, which in a way it was. I did not really feel bad for Pearson, and Ted did not ask that of me: I felt instead the weight of a lost dream of thinking selves left whole and free, a dream that Pearson upheld and also undermined. Ted’s paper appealed to my moral imagination, as well as my intellect. It proved that the history of science could be written as literature.

In the years to come, my formal education led back—again and again—to Ted. His work made the work that I was drawn to possible. I am a historian of quantification and I teach a course titled ‘The History of Numbers in America,’ and so it won’t surprise anyone that I say Ted laid the foundations for what I do. He arrived on the scene as part of that miraculous authorial cohort in the mid-80s who nearly simultaneously published landmark books: Raine Daston, Ian Hacking, Steven Stigler, Ted, and the rest of the Bielefeld gang. Whenever, in years to come, I felt the tug of territorial feeling, whenever I worried that, for instance, too many other people were researching risk, I took solace in the story of that group. There could be strength, and not competition, in scholarly numbers.

But when I say Ted made my work possible, I am not only thinking about his leading role in the study of quantification. Just as important, and possibly more so, was the way he championed the study of science in unconventional settings. In another field I cared about—the history of the life sciences, Lynn Nyhart or Rob Kohler had made the case for finding lost stories in field and experiment stations. Such work made it legitimate for someone like me to go looking for science outside of laboratories, and even outside universities. Ted’s Trust in Numbers has meant many things to many people. For me, it meant first and foremost that a historian could credibly go looking for science in an asylum or the Army Corps of Engineers, or most importantly for my purposes, in a life insurance company or a census office.

I count myself enormously fortunate that Ted counted me as one of his number too. There was no reason for him to ask to read my dissertation in 2009 and even less reason for him to actually do so, sending me within the same month half a dozen meaty paragraphs of comments, questions, and encouragements. “Some kind words from a huge figure” I exclaimed at the time in an email to my partner and parents. It was only the beginning: as Ted proved unfailingly generous—writing me letters of support, stepping in to save my first book after a lacerating anonymous review, and then inviting me to UCLA to give my first talk after that book came out.

I know that Ted intended for his work to help expand our search for science and its histories, because he told me so—at HSS panels and in private. His actions amplified those words. I look at my own cohort of scholars and those who have followed and I think it is clear that he succeeded. Count me among Ted’s numbers, I say, alongside so many others.

Colgate University


The first time I met Ted Porter was in print, when I read his wonderful 1995 book Trust in Numbers. It was undoubtedly at the suggestion of Wendy Espeland that I read it, but I would like to think that I discovered Ted all by myself. It could also be that learning regression analysis from Stephen Stigler cultivated a perverse and mostly latent interest in the history of statistics. Whatever the cause, I wasn’t surprised that Trust in Numbers received such great acclaim, because for me it possessed an alluring set of qualities. First and foremost, it provided a richly documented historical analysis offering some profound ideas about quantification and its applications. In 1991, Wendy and I had published an article on the history of double-entry bookkeeping, so Ted’s discussion of cost-benefit analysis was like the call of the sirens. In addition, however, a distinct authorial personality shone throughout the book: a personality given to very dry, understated wit and self-deprecating erudition. Normally quantification isn’t a laughing matter, but some of Ted’s lines were so clever I just burst out guffawing mid-paragraph. This loud merriment has earned me a few stern glares in the library, and perhaps a ‘shush’ or two.

Then I heard Ted speak in person at Northwestern University, giving a public ‘Ted talk’ at the invitation of my colleague from the history department, Ken Alder. Ted’s authorial personality was there in the flesh, and I was delighted to realize that the man speaking behind the lectern was the same as the man I had met before in print: witty, self-deprecating, learned, and ready to make an important argument. Even more impressively, his erudition wasn’t something stored on his office bookshelves or contained in files and notes: it actually reposed in his brain, ready to be retrieved on the spot!

Spending a year together at the Wissenschaftskollegg in Berlin sealed the deal. Along with other members of the ‘quantification group,’ we were able to think hard about a number of issues, working on separate projects but doing so together. It was a great year, offering the perfect balance of intellectual stimulation and sheer fun. Ted impressed me with his commitment to bicycles and opera. And through Ted I met Mary, another gift of that year. My project eventually turned into a book about the history of credit, published in 2022. Ted’s project became Genetics in the Madhouse, published in 2018. Thank goodness scholarship isn’t a race, because Ted would beat me every time.

Academia is now changing. Increasingly, people maintain a social media presence, and supplant peer-reviewed publications with fights on Twitter, academic selfies, and blog-posts that have a short shelf-life. Ted would not thrive on Twitter, or any such platform encouraging hair-trigger showboating or performative bloviation. He is simply too thoughtful. He isn’t arrogant enough. He knows too much to feel comfortable making caricature summaries or bald assertions. In short, Ted possesses the marvelous and invaluable quality of ‘Ted-ness,’ which is made manifest in all he has done. Where did Ted acquire his Ted-ness? There is some dispute about the matter, and reasonable people can disagree, but it seems to be the result of having grown up in the Pacific Northwest, a breeding ground for rare academics. He is now retiring after a very accomplished career, but he will always remain himself. And what a wonderful self he is! I will be forever grateful that I have had the chance to witness Ted-ness up close and in person, practiced by the man who practically invented it. Thanks to you, Ted!

Northwestern University


When I first encountered Ted Porter he was a shadow; well, a shadow presence anyway. He was in his fourth—and final!—year of graduate school but was already long gone, finishing up elsewhere his brilliant dissertation, ‘The Calculus of Liberalism,’ that would become his first book. I don’t remember if I met Ted that year, but I knew of him, the grad student who would finish in near record time and who managed to earn the admiration and respect of each of the Program’s faculty members (no mean feat). Ted was soon off to CalTech on a postdoc and then a job at UVA before his final landing spot at UCLA. Our paths I know intersected at HSS meetings, both because of our overlapping interests in quantification, measurement, and the human sciences, and because of the notorious Friday night ‘smokers’ where everyone ever connected to the History of Science program and their friends eventually ended up.

Ted, of course, was not a figure one could miss: tall, smart, and with a gravely deep voice, he stood out, even before he spoke, and even more so after, when you realized that he had just asked a profound question or provided some acute insight, often with a little dash of deadpan humor for those attentive enough to catch it. It took me a while to learn that; once I did I delighted even more in the chances to hear Ted speak, knowing that if you listened carefully, you were assured of being amused as well as edified. I don’t have any clear recollections of our early encounters, but I do still remember vividly a talk Ted gave at Princeton. It may have been in Spring, 1992 and I think it was for ‘The Values of Precision’ workshop where I was the commentator. The subject was the role of quantification and numbers in early Victorian life insurance, a seeming snoozer if ever there was one.

The overall theme of Ted’s talk, if my yellowing notes are at all accurate, presaged one of his key arguments in Trust in Numbers, that mid-19th century British actuaries characterized their expertise as deriving not from their mastery of precise quantitative techniques, but rather from their character, as gentlemen of skill and judgment. They did not reject quantification so much as deny it pride of place, arguing that computation and judgment must be combined. The push for mechanical forms of objectivity arose outside of the actuarial sciences, Ted argued, from the demands of lawyers and members of Parliament, what Ted would later characterize broadly as political and administrative culture. What has kept that talk in my memory for so many years, however, was the way he opened it, by pointing out that the practice of life insurance, particularly in the nineteenth century, was based on a paradox. In simple terms, life insurance companies only wanted to sell their policies to people who didn’t want to buy them. If someone wanted life insurance, Ted pointed out, the reasonable suspicion was that they knew something about their health, or were about to engage in some endeavor, that made them a bad risk. Lacking independent ways of determining who was or was not likely to die, prudence dictated being skeptical of those who thought they might expire soon enough to need insurance. The point is still funny, at least to me, and also, I think, profound. How do you entice people who don’t want a product to buy it, and how do you come up with a price that will attract the right sort of person and will also maintain the financial solvency of the company? Ted used this observation as a jumping-off point to do what he has done so well in so much of his work: explore the tangle of science and culture, of quantitative and qualitative, of mechanical and experiential, of hard sciences and so-called soft sciences.

When I think about Ted’s numbers (which I probably do too often, or maybe not often enough), I never think about them alone. In his telling, they always result from people (or instruments) doing work, and are always part of complicated discussions and negotiations among multiple actors. Ted’s numbers are social beings, turned to as often in moments of weakness as of strength. They don’t reveal the underlying nature of the world, whether natural or social, so much as help make it. In some ways they are kind of like Ted himself: powerfully able to help remake the intellectual landscape, and quietly social beings.

I was asked a number of years ago to write a recommendation for Ted for a MacArthur Fellowship (so much for keeping it a secret). I still don’t understand why he wasn’t awarded one. I argued then and would argue now that his work on the history of quantification and statistics more than deserves it. I observed in that recommendation that “Professor Porter stands out in the fields of history of science, science studies, and intellectual history for the range and originality of his scholarship. His work is smart, accessible, and profound in the ways that it reveals the texture of the interweaving of science with other cultural forms. He is not only read in fields well outside of history or science studies (including political science, sociology, literature, and philosophy), but publishes in venues unusual for an historian as well.” Ted’s most recent book, Genetics in the Madhouse, confirms these characterizations of his work, though also reminds me that I forgot to mention at least one critical additional factor: Ted’s work routinely forces us to reconsider what we thought we understood.

What comes next? Personally I’m hoping Ted will do an audio book on numbers and opera. But whatever he turns his attention to, I know it will be full of sharp insights, wicked wit, and probably plenty of funny numbers. Ted always has at least one eye looking out toward the future.

University of Michigan

Karine ChemlaTRUST IN Π

For Ted

In line with Ted’s classic Trust in Numbers, I analyze here the central part played by the number 1620 in the management of grain in early imperial China. Previous scholars have emphasized the cosmological dimensions of the number and the artefact to which it was attached. I argue that 1620, whose decomposition into prime numbers is 22 ·34 ·5, reflects a complex administrative organization allowing different social groups with different mathematical skills to work together to manage grain. Moreover, I suggest interpreting the efforts experts in mathematics made to obtain better approximations of π as related to the project of getting 1620 with π. In my view, these efforts aimed at emphasizing how numbers were crucial to a form of social fairness.

Wang Mang’s bronze hu

The argument relies on the first-century mathematical canon The Nine Chapters. This fact implies that mathematical works of this kind were intimately associated with the imperial bureaucracy. Many clues support this assumption.

In 656, Li Chunfeng finalized his annotated edition of this canon, to which he attached the commentary Liu Hui completed in 263. Interestingly, Li Chunfeng had previously authored historical accounts of measuring units and standards for dynastic histories. My argument combines both types of sources.

In general, the exegeses on The Nine Chapters focus on proofs of correctness of its algorithms. However, on three occasions we see the exegetes discussing the bronze vessel that Liu Xin designed in the early first century for Emperor Wang Mang, and also an inscription that this vessel bore. The vessel was the standard for the capacity unit hu. The inscription stated the numerical value of the diameter of the corresponding inner cylindrical cavity, with a high precision, and the related area and volume, respectively, 162 cun and, precisely, 1620 cun.

Liu Hui’s commentary mentioning the vessel follows three similar problems: cones of grain are formed on the ground (respectively, cones of unhusked millet, soybeans and husked millet mi). Given the circumference of the base and the height, the problems require determining the volume of the heap and the number of hu it contains. The computation of the volume clearly uses an approximation of π: this is the first clue of a link between π and the measurement of grain. The conversion of units of volume into hu attests to a striking phenomenon. In these problems, depending on the grain, the volume stated by The Nine Chapters as corresponding to one hu varies. For unhusked millet, soybeans and husked millet mi, one hu corresponds to, respectively, 2700 cun, 2430 cun and … 1620 cun. Weaving together the commentary and Li Chunfeng’s history of measuring units, we get several conclusions.

These hu could not express capacity. In fact, these units hu measured the ‘value’ of grain, 2700 cun of unhusked millet and 1620 hu of husked grain both corresponding to one value unit hu. Moreover, different hu corresponded to different vessels, each attached to a grain. In fact, in early imperial China, grains were a key product for the economy of the state: taxes were levied, and officials’ wages paid in grain. Determining equivalent quantities for different grains and different states of grain was crucial, and administrative regulations (which are quoted in mathematical writings) asserted numerical values to this effect, expressing them with quantities of volumes or capacity or else with vessels.

Consequently, to evaluate a quantity of grain, one could use the related vessel. One could also use any of the vessels measuring value and simple rules of three. Indeed, every number expressing the volume of one hu could be decomposed into prime numbers exactly like 1620 cun. Hence, converting one unit hu into another put into play numbers made of small factors. Finally, one could shape grain as a cone, using algorithms to compute the volume and then dividing by the volume corresponding to one value unit hu. The latter yielded better accuracy, but required greater mathematical skills.

The administrative organization of the system of grains thus allowed practitioners having different mathematical competences to work together to manage grain. In fact, the pivot of this system was the husked state of grain called mi, which was defined for both millet and rice and thus established a bridge between different grains. Interestingly, its value unit hu was the only one corresponding to the capacity unit embodied by the bronze hu. We see how the system of measurement units was rooted in issues related to grain.

Measuring a cone-shaped heap and using mathematics to evaluate grain yielded accurate results, if the approximation for π was accurate. Having a vessel whose inner volume was exactly 1620 cun was another basis for a fair measurement of the value of grain. One may interpret the inscription carved on Wang Mang’s hu as displaying the effort deployed to ensure fairness. The computation of the best possible value for the diameter of the bronze hu to get a volume of 1620 cun also involved an approximation for π: this is a second link between grain and π. In the fifth century, Zu Chongzhi worked on π in relation to this issue. The second commentary on The Nine Chapters dealing with the bronze hu bears precisely on the area of the circle and can be attributed to him. Zu used various values for π to assess how Liu Xin computed the relationship between the inner diameter of the vessel and the volume of 1620 cun. Considering this computation as inaccurate, Zu offered another value with high precision for the diameter of a vessel measuring 1620 cun.

Arguably, these values gave means to make correct standards. However, the third piece of commentary mentioning the bronze hu, which follows a problem dealing with a cylindrical granary, suggests an additional answer. If grain was essential for the state’s economy, granaries can be compared to banks. The granary in question measures a huge and integral number of hu of husked grain. Could the inscription on the bronze hu also serve to build cylindrical granaries and control the value of the grain contained? This is an open question, which might indicate yet another relationship between π and the evaluation of grain.

SPHERE, CNRS & Université Paris Cité


I had the honor, in 2012, of having Ted on the jury for my Habilitation à Diriger des Recherches (thesis defense) in Paris, together with other distinguished colleagues including Alain Desrosières, the founder of quantification studies in France.1 The Habilitation opens the way to supervision of doctoral students and research projects, and to professorship. The thesis title translates as ‘Compare and Conquer: History and Sociology of International Quantification,’ from Comparer pour mieux régner, and playing on ‘Divide and Conquer.’

The honor of Ted’s participation was twofold. First, being a pioneer of the history of statistics, he provides an inspiring and established framework for contributions like mine. The publication of The Rise of Statistical Thinking 1820-1900 in connection with the work of the Bielefeld group, defines a ‘before and after’ in the field. To wit, and as added evidence of the epistemological transcendence of the book, in the preface Ted acknowledges a giant in the field of the history of science, Thomas Kuhn, for his generous advice. Second, but no less critical, continuing the study of Ted’s work and following up on our exchanges from the Habilitation events, I looked more deeply into a fascinating question; the nature of the link between the statistics of International Organizations (IO) and their power, in comparison to the link between statistics and state power, innovatively analyzed by Porter.

The interaction of two fundamental insights opened rich possibilities for reflection; first, quoting from Ted Porter (Rise, p.17):

The modern periodic census was introduced in the most advanced states of Europe and America around the beginning of the nineteenth century […]. Most often, the chief purpose of this statistical activity has been the promotion of bureaucratic efficiency. […] Until about 1800, the growing movement to investigate these numbers in the spirit of the new natural philosophy was likewise justified as a strategy for consolidating and rationalizing state power” (italics added here).

And the other, quoting Adolphe Quetelet, at the first International Statistical Congress (1853):

Statistics, conceived in a spirit of unity and resting on fixed bases appropriate to all countries, are intended […] to extend its benefits to all countries and to shed new light on the true interests of governments” (translation and emphasis is ours).2

After my initial history and demography degrees in Catalonia, I found in Paris an academic ‘center’ for the development of human and social sciences as well as demographic and statistical theory and practice—and I think that Ted will agree that Paris also has some interesting cafés and cultural sites! Before my PhD, by a stroke of luck, an internship at UNESCO led to several years work there, notably in the Statistical Services, which lasted through my thesis preparation. My ‘peripheral’ origins and ‘outsider’ view of the great powers, as the main actors of the history of statistics, plus my experience as a practitioner, were all helpful to my ‘reconsideration’ of the idea of Quetelet via Porter.

Quetelet’s “fixed [statistical] bases appropriate to all countries” illustrates the international arena’s role in coordinating state development; with the Congress aiming to have censuses taken on a stable and uniform basis, among other recommendations. Statistics, seen as universal, was therefore global. Created later, IOs would come to treat states as the ‘individuals’ in their global series and calculations…

However, the statistical services of the IOs, compared to those of the states, cannot simply be seen as analogous under change of scale, nor merely reproducing and expanding a science that states had already developed. IOs also ‘construct’ states through ‘fixed’ international statistical conventions and ways of working and ‘thinking.’ After World War I, while the League of Nations guided ‘newly created’ and/or ‘peripheral’ states through statistical cooperation, the great powers also progressively complied with data frameworks. They all had to adopt harmonized policies such as free trade and the abolition of forced labor. “Consolidating and rationalizing […] power,” international statistics would finally shed “new light on the true interests of governments”. “True” or, at least, ostensible interests, one might add.

I would like to end this tribute to Ted and his influence, underlining a less examined, more personal aspect of statistics. We all have a special ‘relationship’ with data and its exploration. As a practitioner, I have been captivated, by the beauty of a well-executed statistical analysis, by the unexpected insights that can emerge—just as words artfully composed can illustrate ideas that have not yet found expression. Indeed, one may be struck by how our ability to translate the world into data, and analyze it, is an expression of human genius. Evidently, data is too often used to support preordained conclusions, yet, it takes alternative data and analysis to nurture and maintain, in turn, free and pluralistic debate.

The enigmatic, non-reducible character of statistics underlies Porter’s work, as exemplified in the beautiful expression Statistical Thinking. Alongside Ted, research into statistics lends itself to an understanding of the role of human intelligence in the history of science and moreover in that of culture. The rise of big data is writing a stimulating but disquieting new chapter, with the growth of both knowledge and surveillance capacities. The ‘statistical’ aspect is ever-present, even with recent evolutions, including the Bayesian revival, adversarial learning, etc., while predictions that ‘thinking’ is about to be superseded by ‘artificial’ intelligence are confounded by ‘natural,’ methodological skepticism. The story of statistics continues. As it experiments with new levels of self-reflection, the mystery lives on.


1. The other members of the jury were Alain Chenu who was my sponsor at the IEP in Paris, Corinne Gobin who had supervised my postdoc at the Free University of Brussels, Hervé Le Bras, director of my PhD at the EHESS, Olivier Martin, from the University of Paris Descartes, and Martine Mespoulet, from the University of Nantes.

2. Minutes of the First International Statistical Congress, 1853, p. 19.

Université Paris 1 Panthéon-Sorbonne

Lorraine DastonTHE VOICE OF TED

The first time I heard Ted’s voice was in mind’s ear, but I immediately registered its distinctive timbre, pitch, and tone. I had been asked to serve as an external reader of Ted’s Princeton dissertation on the history of nineteenth-century statistics, a sign of how sparsely that field was populated back in the early 1980s. I had finished my own dissertation on probability and statistics in the Enlightenment only a few years before and was hardly an authority in the field. The dissertation, which would become The Rise of Statistical Thinking (1986), richly repaid the reading. Quite aside from the impressive research across numerous disciplines and intellectual traditions and the originality of the analyses, the dissertation was written with élan and esprit. I often found myself rereading certain sentences, simply for the pleasure of the cadences and the delicate irony. There was something distinctly Victorian about the diction—the symmetry of the syntax, the self-assurance of the judgments, but also the sharp eye for the droll and the odd: imagine a history of statistics written by Trollope. It was unique among all the dissertations I have read before and since in lending itself to being read aloud.

So I was delighted to learn that Ted would be joining the research group Lorenz Krüger, Ian Hacking, and Nancy Cartwright had organized on ‘The Probabilistic Revolution’ at the Zentrum für interdisziplinäre Forschung in Bielefeld during the academic year 1982-83. The project kicked off with a conference at which we all presented our projects, and I can still recall how Ted’s voice—this time in person—reverberated in the ZiF lecture room. It was a voice made for the lectern, the pulpit, or the stage: deep and resonant enough to reach the last row without a microphone. Many years afterwards in 2014, when Ted spent a year at the Wissenschaftskolleg zu Berlin, Ted and I gave a brief reading of science-related texts (as I recall, excerpts from Mark Twain, William James, Thomas Carlyle, and Mary Shelley) at the English Theater of Berlin, and when I ran into the theater’s director a few years later, he was still enthusing about Ted’s excellent stage projection.

At the weekly meetings of the ZiF research group, I learned to listen for a slight change of inflection in Ted’s voice, from the matter-of-fact to the mock declamatory, which signaled a delicious (and deliciously dry) jab at some absurdity or pomposity. The targets could be some long-dead Victorian sage, such as Henry Thomas Buckle, or someone in the room—if the latter, those of us who savored Ted’s subtle humor tried not to giggle in appreciation. When we were not discussing various episodes in the history of probability and statistics, trying to write our books, and discovering the delights of German breads and cakes, those of us who were not native speakers of German were trying to improve our skills in that language. Ted and I had different strategies: I labored, largely in vain, to perfect my accent; Ted was in contrast a demon for grammar. I can recall hilarious contests as to who could pile up the most verbs at the end of a sentence: “hätten müssen können sollen,” and other such monstrosities worthy of Mark Twain. As I recall, Ted almost always won. At the end of that splendid year in Bielefeld, Ted and I tried to keep countenance, helpless with laughter, as we belted out the German version of ‘Home, Home on the Range’: “Zu Hause, zu Hause auf der Heide/ Wo die Rehe und die Antelopen sich tummeln…”.

Thereafter, Ted and I saw each other at intervals, when we wrote a chapter together on how probability had changed everyday life for the collectively authored book Empire of Chance in Freiburg one summer or at History of Science Society meetings. At the former, Ted and I had to be talked down by our co-authors from various forms of literary folie à deux: only with great reluctance did we agree to strike one of our subheadings about the effects of some quotidien intrusions of statistical thinking: “Insult to Injury.” At the latter, I doubly cursed the program chairs who put Ted and me in competing sessions, often in adjoining rooms: first, because I had to miss Ted’s talk, always an HSS highlight; and second, because I could barely deliver my own, my thin soprano being no match for Ted’s basso profundo reverberating through a thin wall or partition.

I continued to follow Ted’s evolving authorial voice: the brilliant analyses in Trust in Numbers (1995) (my favorite chapter being the one contrasting the haughty noblesse oblige of the French Polytechniciens and the devious cunning of the U.S. Army Corps of Engineers, driven to cost/benefit analyses by a stingy Congress); the clear-eyed but sympathetic portrait of Karl Pearson (2004). I reread the latter several times, first for the insights into Pearson’s work, then for the insights into the life. The latter were evoked with remarkable sensitivity. Pearson was not an easy man to like during his lifetime and his legacy was in many ways baneful. Yet although Ted’s exquisite sense of irony never failed him as he recounted Pearson’s youthful passions and pretensions and his later feuds and obsessions, Ted wrote with a depth of understanding for human foibles rare in scientific biographies, a genre that tends to polarize into vitae of sinners and saints. To me, this book marked a shift in Ted’s voice, still attuned to ‘nonsense on stilts’ and downright silliness in the historical record, but more reflective, more appreciative of the hardships of being human.

Ted’s deadpan is famous, and he rarely tips his hand in a bald judgment, whether in person or in prose, preferring to let his carefully constructed accounts speak for themselves. Yet the one time I have heard Ted’s voice quiver with something like indignation seems to me to speak volumes about the vision that has informed all his work, from The Rise of Statistical Thinking (1986) to Genetics in the Madhouse (2018). It was at a Wissenschaftskolleg colloquium delivered by a geneticist, who had made grand claims about the future of genetic engineering. In the discussion, Ted pointed out how such scientific swaggering had had a history of causing vast human harm. When the geneticist impatiently waved aside such objections—“We know better now”—Ted retorted, his voice rising uncharacteristically: “Don’t you think some humility is in order?” That intolerance for pretension and arrogance masquerading as knowledge, with what in German is called Besserwisserei, seems to me to inform much of Ted’s extraordinary oeuvre, an earnest current running beneath the ironic surface—the voice of Ted.

Max-Planck-Institut für Wissenschaftsgeschichte, Berlin


For as long as I can remember a newspaper clipping was posted on Ted’s office door on the fifth floor in Bunche Hall. Visible to everyone who bothered to stop and look, it read:

PORTER is more than just about numbers”

What a lucky find! But who, I often wondered, was this other Porter? Perhaps an athlete with impressive stats? The clipping itself did not provide any clue as the source, date or other potentially revealing margins were carefully cut out. Ted himself, when questioned, remained sibyllic about it. A Google search reveals that there was a two-time NCAA collegiate wrestling champion and football player called Dave Porter. Could this be him? Or do these numbers refer to Porter beer? To Porter airport? Or are these the stats of a female body? A Google search for the whole phrase promptly brings up “Porter, Trust in Numbers.” But could it really be that this came from an article about Ted with his last name printed in such bold letters? Perhaps it’s better to ask: what does the newspaper clipping on Ted’s door say about the Porter we know?

Puns amuse Ted. Putting this phrase at the outside of his office door is an invitation to enter with a smile. And where others may try to impress visitors with gold-framed awards and other paraphernalia of personal success, this clipping seemed to want to gently deflect from the numbers and the book that are so often associated with his name. At the same time perhaps, there is a hint that the door (porta in Italian) leads to a place where numbers become reconnected with their historical realities and lose their seeming absolutism, as their rhetoric is carefully analyzed.

Unfortunately, the last time I looked, the clipping had disappeared. When I asked Ted about it, he remembered taking it down but thought it was unlikely that he had thrown it away. I hope he finds it again, not least so I can make sure I remember the phrase correctly. Of course I did not tell Ted why I was so interested in it and I don’t think he suspected anything.

University of California, Los Angeles


One day back in 2017, when Ted came to visit us in Paris, he offered to my wife Aurélie and me a present: a tin can with a label reading ‘Cougar Gold.’

We opened it and, much to our surprise, discovered it was cheese! Cheddar cheese, made at the creamery of Ted’s home state university, WSU. His gift was very considerate and personal but, I have to confess, Aurelie and I were a little worried—how on earth would we be able to thank him after actually eating it!? But then came the real surprise, after we had actually tasted it: the cheese was smooth and creamy and packed with delicious flavor!

This gift, to me, says a lot about Ted. It was thoughtful and funny, the same way Ted is, of course. But it was characteristic of Ted in another way too. It exemplified Ted’s unique way of playing with perspectives. It is the French who are expected to offer cheese to their American friends, not the contrary! But for Ted, the reversal of even the most generally held assumption is always a possibility. So, his present of canned cheese was more than a considerate, funny, and personal gift. It was a demonstration of how things can always be seen from another perspective.

Ted, of course, is an expert at changing around perspectives when it comes to food. He is a refined gourmet and as good a cook as any Frenchman. In Berlin in 2013, when we were both fellows at the Wissenschaftskolleg, Ted and his partner Mary Terrall—a Professor Emeritus of History at UCLA—volunteered to help me make foie gras, with Aurelie overseeing operations. To do this, you need to remove the nerves, a complicated task that involves plunging your hands deep into the fattened goose liver. Some people are grossed out by the process. Not Ted. He found the whole thing highly amusing! The following year, when we relocated to LA, where I was a visiting professor at UCLA for two years, we got to see a lot more of Ted and Mary. One of the first things Ted did to welcome us to California was to invite us for lunch at Mary’s place (we had many delicious meals together, but that day Mary was travelling in Europe). The menu he had prepared included a mixed beetroot carpaccio, scallops with kumquat sauce, and Santa Barbara prawn tempura! His unforgettable cuisine—a word originally borrowed from the French—took our Californian culinary experience to new heights!

But there’s another, more intellectual kind of food I wanted to talk about today, because Ted’s brilliant ability to play with perspectives is also clearly visible in his work. Take his publication Trust in Numbers, especially chapter seven, which I assign my students every year. The chapter shows how the US Army corps of engineers went from having little sway over political decision-makers—especially compared to the French engineer corps, the Ponts et chaussées—to becoming a powerful political voice via quantification-based cost/benefit analysis. In other words, the Army engineers’ ability to make ‘objective’ decisions gave them power in the political arena. Contrary to the belief whereby quantification is a ‘tool of power’ to be wielded by the government, the chapter concludes that statistics are also and at the same time a ‘tool of weakness’ to be wielded by less powerful hands—in this case that of the engineers. These ‘weaker’ parties are able thus to resist and even, at times, to gain the upper hand. Ted’s line of reasoning turns Foucault upside down. It is not a criticism of statistics but rather a perspective placing the focus on the liberating properties of statistics. This postulate is at the heart of the concept of ‘statactivists,’ a term we coined with Isabelle Bruno, an associate professor in political science at the University of Lille, and the artist Julien Prévieux. Statactivists are activists who use quantification tools to defend their cause, and who frequently have to invent parts of their statistical methods. Most often, they are neither specialists nor bureaucrats, like the staff of the Army Corps of Engineers. However, like these latter, they find themselves in a weaker position and make use of quantitative tools to try to gain greater power and freedom.

Here is another example of Ted’s ability to flip perspectives. In the late 1990s, while I was at the Ecole des Mines with Bruno Latour, we invited Ted to the CSI in Paris to give a talk. After the seminar, while we were out for drinks with Ted, Fabian Muniesa, and a number of other participants, Ted all at once turned to Fabian and asked without warning or a lead-in, “So tell me, Fabian, what exactly do you mean when you say that the economy or statistics ‘performs’ the world?” What a question! There was a consensus at that time in Paris regarding the concept, with which we were all supposedly familiar and in agreement. But again, Ted, who is clearly convinced of the social impact of quantification, was suggesting another more realist perspective of how numbers behave. Observing Ted’s falsely naïve question regarding this commonly accepted notion, one that he himself never used, inspired me to play with it as well.

Lastly, to speak about Ted inevitably brings me to his relationship with language. In all of his written work, his mastery of language is clearly visible. I am constantly amazed by his skillful use of narration, story arcs, and eloquent examples, by his attention to detail and precise use of vocabulary. I always tell my students in France: “Pay attention when you read Ted Porter. He writes in English not in basic Globish.” I particularly admire the way Ted seamlessly knits various perspectives into a subject matter. His texts appear to be produced from a single cloth but, in reality, are comprised of multiple stitched-together viewpoints. These perspectives are so skillfully articulated that the reader isn’t immediately aware he has switched from one perspective to another.

His masterful use of English goes hand in hand with his taste for foreign languages. In Berlin, where we were immersed in French, German and English, Ted and I often had amusing conversations about various linguistic ‘fun facts.’ We’d play with English language homographs—desert vs. desert, close vs. close, and content vs. content—or laugh about our different pronunciations of the German genau, pronounced ‘Ge-now’ in Ted’s mouth and ‘Genaho’ in my more Gallic attempt. In LA, Ted coined the portmanteau term ‘Didina’ in reference to our respective last names, ‘Didier’ and ‘Slonina.’ Our very spacious home was therefore dubbed ‘Chateau Didina’ by Ted. But even more impressive to me is the fact that his mastery and love of words and linguistic cultures can be seen in his unique ability to analyze and unpack the very specific jargon of mathematics and statistics!

To me, Ted’s love of different languages and his taste for switching up perspectives are two sides of the same coin. Because languages—including the languages of quantification—are tantamount to opening perspectives on the world, and Ted, as a true cosmopolite, has a genuine love of embracing all of them, one after the other.

CNRS/École normale supérieure - PSL

Wendy EspelandFACTS

Ted is generous. Ted is loyal. Ted is meticulous. Ted is honest. Ted wears a lot of khaki pants. Ted is an amazing friend. If you need a last-minute speaker, Ted has his bag packed. It could be Jersey. It could be Rome. He’ll be there. And now…. A Few Fun Facts About Ted.

  1. I can make 64 words from Theodore M. Porter. The most notable include: Meteor Poem Method Mother Terror Order

  2. Ted played the tuba in the marching band.

  3. Ted does an amazing impression of a turkey.

  4. Ted puts the buff in opera.

  5. There is a Ted Porter elementary school in Fontana California.

Haiku for Ted

For guidance we turn
to our most unflappable friend.
We all trust in Ted.



SEPTEMBER 16, 2022

In Ted we Trust
to teach us Objectivity
Mechanical, yes, but also

His Motto is: Be Fair
to bolster our Receptivity
in Ted we Trust,
to teach us Scholarly Humility.

In Ted we Trust
to help us grow Community
for Freaks like us, to foster Nerdy Unity.

Cost-benefits. Annuities. Eugenics and
Insanity. Ted Finds a way to celebrate

In Ted we Trust.

Love from,
Friends, Scholars, and assorted Personalities
Northwestern University


Back in 1982 Ted and I met for the first time at the Center for Interdisciplinary Research in Bielefeld for a year-long workshop on the Probabilistic Revolution.1 We were among the youngsters in a group of eminent scholars, and ended up as co-authors of the volume The Empire of Chance.2 The Empire’s currency is statistics, backed by objectivity, prestige, and trust. While in Bielefeld, Ted worked on his first book, The Rise of Statistical Thinking 1820-1900, in which he analyzed how the language of probability transformed the thinking of social scientists, biologists, and physicists. For me, the year at the Center was life-changing, expanding the small world of a psychologist to the large world of the history of science.

What can I contribute to this celebration of Ted and his achievements? My first impulse was to write about his brilliant gift of parodying the German language by amassing scores of verbs at the end of sentences, or about his unique technique at the ping-pong table. But instead I will provide a few examples that show why his topic, the rise of statistical thinking, remains so timely in the twenty-first century. By now, numbers have become the language in which many politicians, journalists, and the general public talk. But understanding these numbers is another thing.

“We send the EU £350 million a week. Vote Leave.” That shocking figure, displayed on the Leave Campaign’s iconic red bus during the 2016 Brexit referendum, may have tipped the narrow balance in its favor, resulting in 52% votes for (versus 48% against) leaving the EU. However, the figure was unrealistically high and ignored what the UK then recouped from the EU. Had it been expressed as 75p per day and per person, as British statistician David Spiegelhalter once proposed, it would have startled few voters. Since time immemorial politicians have been accused of deliberately twisting the facts. But the question is, do they actually understand statistical numbers?

Four years before the Brexit referendum, the Royal Statistical Society (RSS) investigated this question with the voluntary help of 97 MPs. By no means did the MPs form a representative sample, and most of them felt confident dealing with numbers. The first question posed to them was:

If you toss a fair coin twice, what is the probability of getting two heads?

If you are not sure, you are not alone. Barely 40 percent of the MPs correctly figured out that the answer is 1 in 4, or .25. Almost half of the MPs (45 of 97) believed the probability to be .50. Conservatives fared better than Labour MPs. When this degree of innumeracy became known, 220 candidates seeking to enter the House of Commons signed up for a workshop on how to interpret statistics in public life.

Ten years later, in 2022, the RSS repeated the test with 101 MPs. Statistical thinking had improved: This time, 50 percent of Conservatives and 53 percent of Labour MPs got the answer right, although newly elected MPs performed worst.3 Once again, the 2022 group was self-selected; in a representative sample of the UK adult population, only 25 percent found the correct answer.

What about Covid-19 statistics? After all, the numbers were what fueled our hopes and fears during the pandemic. In their 2022 test of MPs, the RSS also posed this question:

Suppose there was a diagnostic test for a virus. The false-positive rate (the proportion of people without the virus who get a positive result) is one in 1,000. You have taken the test and tested positive. What is the probability that you have the virus?

The answer is that no correct answer is possible on the basis of that information alone. One would also need to know the hit rate of the test, and the base rate of infected people. Only 16 percent of MPs realized that; the others came up with a probability such as 999 in 1,000. This error is known as the prosecutor’s fallacy, that is, confusing the probability of a positive test given no infection (or a DNA match given no guilt) with the probability of no infection given a positive test (or no guilt given a DNA match). On this particular question, the MPs were hardly better than the general UK public, 15 percent of whom responded accurately. My point is not simply lack of statistical literacy, but that most do not suspect they suffer from it. For instance, former prime ministers Tony Blair and Theresa May publicly presented health statistics that they systematically misunderstood. 4 The extent of statistical illiteracy resembles a raging pandemic that has gone unnoticed.

Does it matter whether politicians and experts understand the basics of statistics? In November 2021, the host of a popular German late-night talk show presented a graph clearly showing that Covid-19 vaccination protects people over 60 from infection and death. Yet the host and his guests, including a virologist, jointly misread the numbers and left millions of viewers with the impression that vaccination did not work. Lack of statistical thinking can be as detrimental as conspiracy theories to public health. I have held CME courses for over a thousand physicians as well as workshops for U.S. Federal judges, and learned at first hand that neither group receives much in the way of statistical education. At the end of medical school, most graduates are not sure what basic concepts such as false positive rate, relative risk reduction, and five-year-survival rate mean.5

In the Empire of Chance, we documented the degree to which numbers rule the world, from medical diagnostics to baseball statistics to match probabilities in courts. Yet those born into the empire of chance are like non-nationals who struggle to speak its language. We teach our children the mathematics of certainty—algebra and trigonometry—but rarely the mathematics of uncertainty, statistics. We have a long way to go before becoming homo sapiens numerus, in love with and curious about numbers. On the last pages of the Empire of Chance, Ted and the rest of us introduced a term for this new attitude toward life: statistical Lebensgefühl—the delight in living with uncertainty.


1. Lorenz Krüger, Lorraine J. Daston, and Michael Heidelberger, eds., The Probabilistic Revolution: Vol. 1. Ideas in History (Cambridge, MA: MIT Press, 1987). Lorenz Krüger, Gerd Gigerenzer, and Mary S. Morgan, eds., The Probabilistic Revolution: Vol. 2. Ideas in the Sciences (Cambridge, MA: MIT Press, 1987).

2. Gerd Gigerenzer, Zeno Swijtink, Theodore Porter, Lorraine Daston, John Beatty, and Lorenz Krüger, The Empire of Chance: How Probability Changed Science and Everyday Life (Cambridge, UK: Cambridge University Press, 1989).

3. Royal Statistical Society, ‘New RSS survey tests statistical skills of MPs.’ Last modified February 11, 2022.

4. Gerd Gigerenzer, G. (2014). Risk Savvy: How to Make Good Decisions (London: Penguin Books, 2014).

5. Miriam A. Jenny, Niklas Keller, and Gerd Gigerenzer, “Assessing Minimal Medical Statistical Literacy Using the Quick Risk Test: A Prospective Observational Study in Germany.” BMJ Open, 8 (2018):e 020847.

Max-Planck-Institut für Bildungsforschung, Berlin


Something about Ted Porter and his unique talents crystallized for me when I heard him talk about ‘funny numbers’ more than a decade ago.

My eyes had already been opened as a graduate student to the politics of quantification, largely through Ted’s work—probably introduced to me in a history of science seminar (or by osmosis?) at Princeton, his graduate alma mater.

Ted’s magisterial Modern Social Sciences volume in the Cambridge History of Science series, co-edited with Dorothy Ross, would likewise ground my understanding of the field as I began teaching my own graduate seminars at Penn. That thick green volume still sits on my shelf next to Trust in Numbers and The Rise of Statistical Thinking, recently joined by Genetics in the Madhouse. More than most of the books lining my office, Ted’s slip on and off the shelf on a regular basis, whether for my teaching or my own edification.

At some point early in my career as an assistant professor, I first met Ted in person. I was appropriately intimidated, until it became clear to me how kind, generous, and genuinely interested he was in others’ ideas, no matter the source.

I’ve conducted some archival reconnaissance on my own c.v. and inbox and I can’t quite reconstruct this next event. But I believe it was either at a workshop at the University of Chicago or at an HSS meeting, circa 2010, that I first heard Ted talk about ‘funny numbers.’ It was a brilliant presentation, delivered with his trademark dry wit and analytical panache. I believe it was at that moment that I grasped what is so very distinctive about Ted’s scholarship, more unusual even than his role in creating an entire field.

It’s this: Ted is a very funny historian.

A version of that talk on funny numbers was published in the journal Culture Unbound. Here is an excerpt from the abstract:

The struggle over cure rate measures in nineteenth-century asylums provides an exemplary instance of how, when used for official assessments of institutions, these numbers become sites of contestation. The evasion of goals and corruption of measures tends to make these numbers ‘funny’ in the sense of becoming dishonest, while the mismatch between boring, technical appearances and cunning backstage manipulations supplies dark humor.

Let me ask: What’s not to love in an abstract that takes up cure rates and institutional assessments but manages to work in “cunning backstage manipulations” and, furthermore, promises “dark humor”?

Historians are often good writers. But I think they generally underestimate the power and craft of word play—the way fresh metaphors and juxtapositions aid us in seeing what we did not or could not see before.

Not so Ted. His insights, historical and conceptual, have always been buoyed by his precision with words. But they have been equally indebted to a keen wit—his way of startling you into understanding with an apt (and often very funny) observation. The ‘statistical alchemy’ effected by a ‘well-timed transfer’ of a person to a mental asylum from the poorhouse so as to improve an institution’s stats is one example from that same essay. Or the fact that because insanity was known as a disease of civilization, French and English accountants of madness were baffled that “poor, rural Norway, with its fjords, forests, and rural poverty” could be so far ahead in the rankings. Or Ted’s portrayal of the offstage shenanigans of bureaucrats, which he compares to theatrical plots of Kiss Me Kate and Noises Off. Referring to the machinations of hedge funds and arbitrage (to which he has drawn a line from asylum cure rates!), Ted notes, “Off stage, the madness gradually extends its empire until the onstage action also is infected by the chaos.”

It’s deft descriptions like these—carrying us from the board room to the Vaudeville sketch, nineteenth-century asylums to twenty-first century financial markets, in a well-placed sentence or two—that set the stage for Ted’s punchline: “Whoever can exploit the ambiguity of measures to fulfill numerical targets without having to expend resources on the thing measured enters into the domain of funny numbers.” And furthermore: “These furnish a new theater of insanity, one that is uniquely funny because the deception and manipulation that we see offstage have made possible the fine displays of order and tranquility on view.”

What strikes me in re-reading this essay is the exquisite wielding of humor to produce its opposite: a sober reckoning with the technical (and therefore social and political) architectures we live within. The financial collapse of 2008, tightly linked to funny numbers, was both comic in Ted’s sense and tragic. To quote him again, the “intrinsically comic situations” that quantitative manipulations produce are not just funny; they are “painfully funny.”

The same is true of Ted, a master at narrating the lives of numbers, charts, and tables with sly irony but deadly seriousness.

I titled this set of reflections “funny historians” to gesture to Ted’s formulation of “funny numbers.” But the title probably ought have been singular rather than plural—in point of fact, there just aren’t that many funny historians. Ted himself, of course, is not just singularly funny. He is a singular thinker, scholar, and colleague: truly one of a kind.

Vanderbilt University

Morgane LabbéAT THE BORDER

I met Ted three times—first through the French reception of Trust in Numbers, then at the MPIWG in Berlin when his most recent book had captured so much attention, and finally shortly afterwards, during a one-day trip between Berlin and Szczecin to cross the border. Thus, I took my first steps in Poland with Ted, not knowing then that I would return there so often, every year, for twenty years to make it the field of my research in the history of statistics. I saw Ted again in Paris, during his frequent visits there to his many friends and colleagues—indeed so regular, that we often asked each other “When is Ted coming? And Ted, as soon as he got off the plane after having flown over the American continent and the Atlantic, would join us, with his disconcerting casualness, in a seminar, or at the bistro to sit with us in front of a blanquette or a chocolate fondant, as if he had always lived here. But friendship never eclipsed the value of his research in the history of statistics and for me, it was again a story of borders.

The success of Trust in Numbers has made us forget how much Ted’s previous book, The Rise of Statistical Thinking, gave a new place to a cursed chapter in the history of statistics, that of Germany. To those who were interested in it, as I was, nineteenth-century German statistics seemed to have been reduced to a routine Weberian production of figures, skeptical of probabilistic reasoning and causality and therefore banished from the glorious narrative of the emergence of statistics. Between the eighteenth-century university discipline with its rigid cameralist framework and the technology of the Nazi dictatorship in the twentieth century, nineteenth-century German statistics had been reduced to a supposed Napoleonic foundation of which the Prussian Bureau would have been only a pale imitation. In his book, Ted exhumed forgotten German statisticians and gave them a right place: Ernst Engel had not only found a “law of consumption," under the influence of Quetelet; he conceived of a census methodology as a tool for describing a changing social world. Ted also challenged common views on the German statistical bureaus, such as the Prussian office, that did not correspond to the ideal-typical panopticon. Administration and science were intertwined at all levels, therefore also subordination and independence. This brand of statistics gave rise to new kinds of knowledge and therefore not only increased social control but also shaped social change. Ted encouraged readers to study the bureaucracy as a place of innovation, and still today this proposal remains original and productive as shown by historical research of young scholars on the bureaucracy of the Habsburg or the Mughal Empires.

Ted’s work on objectivity as an impersonal strategy has made it possible to think of quantification in terms of historical epistemology, as a specific way for establishing proof and validation. The impact in France of this epistemology of quantification has not, in my opinion, been properly emphasized. One exception was Alain Desrosières, who was always ready to point out the contribution of the so called ‘Bielefeld group.’ Following him, I argue that thinking of objectivity as a moral category to produce impersonal knowledge helped us to escape from the impasse of constructionist approaches and binary oppositions—real/constructed or true/false—that characterized all-too systematically the critical stances on statistics in the 1990s, whether in public life, politics or the social sciences.

Ted’s intellectual commitment and the political engagement of a French historian or sociologist of statistics have little in common. Yet for both, the question of the growing power of quantification in public affairs is a major and central question. Today Trust in Numbers has become a reference for a new generation of students and scholars aware of the issues at stake in the growth of databases and the proliferation of algorithms in the governance of public and private things. But Ted’s book is not a textbook! He questions the success of quantitative methods in modern times, but he does not offer simple answers. For instance, he suggests that quantification, as a strategy of impersonality, is more suited to a regime of weak power than to an authoritarian regime. I have always considered this statement as a challenge for anyone working on Eastern European statistics. Once again, Ted prevents us from thinking in terms of political determinism and encourages us to pursue the research in the field.

I close my contribution with another border history, from my book La nationalité, une histoire de chiffres, that exemplifies how inspiring Ted’s way of thinking on this issue has been for me. At the Paris Peace Conference in 1919, a commission on the future borders of Poland had been set up, bringing together French, British and American experts to decide on how to draw them by means of ‘ethnic statistics.’ When they came to the borders of Eastern Galicia, a former Habsburg province, they adopted a different way of decision-making. Deciding that the majority of the population, called Ruthenians, lacked a national awareness, they decided to delimit areas where there was a ‘statistical doubt,’ in other words where statistics was considered useless for decision-making purposes. Instead, they promoted infrastructure and topographical features, or plebiscites. Indeed, it was the chairman of the session, a French general, who imposed this authoritative conception of a ‘statistical doubt’ and opposed the ‘trust in numbers’ of the experts in the force of technical and military arguments. We know today how weak this tool of a strong power actually was.

École des haute études en sciences sociale


I can say, without too much exaggeration, that I owe my career as a historian of science to Ted Porter. More than twenty years ago, I was a newly married mathematics and physics teacher in a Los Angeles high school grappling with the realization that an earlier career, in the music industry, writing and working with America’s number one trucking entertainer Joey Holiday, was not compatible with the ambition to start a family. I was therefore trying to go back to school. That school had to be UCLA, because my wife was an Angeleno with an established career in Los Angeles. But, understandably given my lack of experience, UCLA had rejected my application. Undeterred, I decided to send an email to one of the historians of science at UCLA, a Professor Theodore Porter, to ask for advice about reapplying. To my utter astonishment, the professor not only replied but also invited me to UCLA to meet him in his office, where he told me that if I was serious about entering the PhD program that I should attend some undergraduate lectures he was giving on the history of science and write some papers. This was more than I could ever have hoped for, and I happily agreed. Thus, over the next couple of months, I spent two lunchtimes a week dashing up Olympic Boulevard from the high school at which I was teaching to UCLA to hear Professor Porter speak. I also began visiting him in his office to talk about the history of science and the essays I was writing for him. At the time, I knew virtually nothing about who Professor Porter was, and looking back now, I am amazed at his generosity.

Due to Professor Porter’s support, I was fortunate enough to be admitted to the UCLA graduate history program. To celebrate, Nonny (my wife) and I decided to invite the professor and his family for dinner. Along with the Porters we also invited two good friends of ours, an artist and her husband, who worked in the film industry. A little older than us and successful in their respective fields, Nonny and I thought that these friends would help provide the necessary combination of seriousness and conviviality for entertaining the formidable, and for me at least, intimidating Professor Porter.

On the evening of the dinner, it took a little time for nerves and reservations to melt, but just as Nonny and I had hoped, the artist and filmmaker were not shy about sharing their thoughts on a wide range of topics and gradually opinion and conversation began to flow. I do not remember the details of that conversation, but I do recall that as it came alive so did the professor, who began subjecting every assertion to a penetrating and funny wit. My abiding memory of that dinner was a moment close to the end, when the filmmaker, now with his back to the wall, stood gamely returning fire to the professor’s relentless retorts. I also remember, after everyone had left, turning to Nonny and asking, “What have I let myself in for?”

I need not have worried. The next five years, spent reading, discussing, and writing about the history of science with Professor Porter in his research seminars, working with him as one of his teaching assistants, and becoming his friend were some of the most rewarding of my life. Dinners with Ted, although never routine, now became more familiar, and with that familiarity came a deeper appreciation of Ted’s humor. Ted’s wit is not negative, it is expansive. Ted, I realized, was not interested in shooting opinions down but sending them up, so that they might help us to see a little further. To write, as Ted did, “But Uriah Heep was humble too” to the claim once made by historian of science John Heilbron that European fin-de-siècle scientists had retreated into descriptionism to protect themselves from the greater powers of land and church, was not to puncture and deflate Heilbron’s assertion, but to expand upon it. Retreats are, after all, often tactical, and the end of the nineteenth century also saw the birth of eugenics. Humor and the pointed remark, at least the way Ted uses them, drag the messy backstage comedies, the false starts, the embarrassing moments, the unquantifiable and irrational and therefore oftentimes disconcertingly unique, back into the light. What Ted taught me was to appreciate what he calls the “mercifully heterogeneous” world that, he insists, often shows up, “like the fool in a play, or the unwanted relative in a farce,” in even the driest scientific paper. With little concern for anachronism or even paradox, Ted encouraged budding historians of science like the younger me, to be “modern humanists,” to look beyond the data of measurement, testing, or a curriculum vitae to the life lived. That deep humanism, I like to think, also informed the very generous response Ted gave to the naïve and hapless young man that sought his help more than twenty years ago. There was certainly comedy in that first dinner. But despite its awkwardness, I remain profoundly grateful for it. It heralded not only the beginning of my career as a historian of science but, much more importantly, my friendship with Ted.

California State University, Fullerton

Martha LamplandTED PORTER

I could never understand what numbers meant. I could add and subtract, multiply and divide, even do a little algebra, but the fascination others had with numbers escaped me. They looked flat, uninteresting, certainly less interesting than words that had depth and complexity. And yet I knew people who, with stars in their eyes, could wax poetically about the beauty of math. I was at a loss. And then I started to read Ted’s work. Ted kindly walked me through the complicated histories of numerical calculations, stories full of people with colorful personalities and quirky expectations. I learned that the shifting configurations of numbers over time could be traced to hard fought battles over right and wrong as well as better or worse. I learned that specialists of various stripes used numbers differently, and for good reason. I also learned that not everyone was as enamored of numerical conventions as I had thought. This was liberating. Ted’s insistence on asking questions about the prestige of quantification or the revaluation of probability assured me that my hesitations about quantification could be explained, while also demonstrating that the ambition of those fiddling around with numbers wasn’t entirely foolhardy. In 2001 I had the privilege of spending a quarter with Ted in a research seminar at UC Irvine, where I witnessed his measured skepticism and insightful criticism firsthand. And what a droll sense of humor! Watch his face and see the witty quip percolating, then sit back to enjoy the fun. Ted ushered me into a world where I felt safe delving into the history and pragmatics of numbers, and he did so with aplomb. For this I shall always be grateful.

University of California, San Diego



I met Ted Porter during the academic year 1990-1991 when we were both visiting scholars at the science studies department of UCSD. Trained initially as a biologist, I then shifted to research in the history and sociology of science, and had high hopes that a year in a renowned science studies department would greatly enhance my skills in the new domain. Moreover, since we made a house exchange with a US professor who lived in San Diego’s semi-rural suburb, Alpine, I was looking forward to an idyllic life in a sunny and beautiful spot. Unsurprisingly, things did not turn out as planned. The weather was indeed great, the nature too, but other aspects of life in Southern California were much more complicated. Married to an American, I had often visited the USA for family and work, but visits to New York, Boston, or Philadelphia did not prepare me for life in a small, conservative Californian community. The neighbors were very kind and welcoming: they were also charismatic evangelicals, revered the military, adored firearms, and pitied people who lived outside the US. My husband, a pure East Coast product, was not of great help; he was often as mystified as I was.

We came to the US with four young children who had to adapt not only to a new language—they spoke only rudimentary English—but to an alien and puzzling social environment. In the local public school (coming from France, we did not view private school as an option), they had to answer questions like “You are from France or Paris?” “What language do they speak in France?” or “Do they have cars/ TV/ jeans there?” One of my daughters, then in second grade, inadvertently blurted that her parents often drink wine with dinner; she was labeled a child of alcoholics. Another daughter was disbelieved when she said that her parents do not belong to any religious congregation. Discussing with other mothers at PTA meetings, I kept making blunders. My response to the frequent comment “It must have been terribly difficult for you to return to work when your children were small”—“No, because luckily we had places for all our children in a municipal day care center” was decidedly wrong. My answer to the question “How do you cope with young children and work”—“I do not cope; I survive between disasters” was even worse.

The UCSD department, I found, was problematic too, although for different reasons. The department was warmly recommended to me by Bruno Latour, who at that time had a part-time appointment there. Bruno was right about the high quality of the department’s scholars. Alas, he had omitted to tell me about tensions and problems within the department. I found myself in the midst of conflicts and fights that I poorly understood, angry exchanges on topics I ignored, and acerbic allusions to past events I knew nothing about. Foreigner and novice to science studies, I often felt utterly lost. Thankfully, two scholars in the department who were not involved in the local ‘science wars,’ helped me to remain sane, and to learn a lot: Chandra Mukerji and Ted. Chandra taught me about the importance of detailed investigations of the material cultures of science and provided an amusing feminist analysis of the fights among the department’s ‘Big Men.’ Ted also occasionally offered dry, ironic comments on the department’s infighting, but above all opened to me the whole area of study of the history of quantification and statistics. I learned that precision has a history, as does the striving to produce objective knowledge, and that the different methods to achieve these goals are at the very center of the enterprise called modern Western science.

At some point, Ted gave me to read the last chapter (the ninth) of Trust in Numbers, a book he was writing in San Diego. I was very impressed by this text, especially its discussion of the nature of ‘scientific communities,’ which echoed and enriched my interest in Ludwik Fleck’s notion of ‘thought collectives.’ Fleck provides insights into the internal functioning of scientific communities. Ted’s chapter added the essential dimension: the need to study how these communities interact with other social actors, and how they attempt to legitimate the knowledge they produce. He introduced the key differentiation between closely knit communities, which achieve coherence through homogeneous socialization, dense personal ties, and a high level of trust, and loosely structured communities, strongly dependent on external validation, which count on formal, often rigid rules to achieve some measure of authority. He also explained that the first kind of scientific community is the exception, rather than the rule. The main message I derived from the last chapter of Trust in Numbers was that science is—mostly—a fragile and uncertain domain, deeply entangled with other areas of social, political, and economic life. Historians of science who study such a brittle domain can produce only imperfect, partial, and situated knowledge. It was and still is, an oddly comforting conclusion. Thank you, Ted.

Institut national de la santé et de la recherche médicale, CNRS


Dear Ted,

We once talked about the straightjacketing of grant-proposals in which you have to state not only what has been done, what you will do, why and with whom, but also how you will do it (the ‘methods’ section), and with what results (the ‘deliverables’). Andrew Ure, who was even more enthusiastic about the factory system than Charles Babbage, would have loved this sequencing of activities, which resembles the production process of an Awkright textile mill rather than the free intellectual journeys in the eighteenth-century Republic of Letters. In a jest, you explained your own method as: “I have a question, I go to the archives, I write a book.” I suppose you consider my reference to a liberal Republic of Letters misplaced romanticism, as the intellectual freedom of the few was not as free as sometimes claimed and rested on the ‘hard times’ of the many.

Then again, am I wrong in thinking that in much of your work, you were intrigued by conservative critics of the social order who leaned towards, or explicitly embraced, an idealized past untroubled by its modern sins? When we started collaborating in the project on the history of scientific observation, directed by Lorraine Daston at department II of the Max Planck Institute for the History of Science in Berlin from 2006 until 2011, your initial suggestion was to write about the French flaneurs who strolled the Paris arcades with their turtles on a leash to demonstrate that their freedom was unaffected by the mechanized processes of production that kept the working class in chains. And it came somewhat as a surprise that you exchanged these romantic observers of the new industrial and consumer world for Frederic le Play’s budget studies in the Harz. In the published version, you draw a contrast between the “neutral and detached” way of observing by the flaneur and the census taker and Le Play’s mode of close observation.1 I can see how this contrast helped you to understand Le Play’s shift from statistical numbers to the intimate method of budget monographs as a romantic longing for forlorn social ties. You observed that tracing the budget of the mining families in the Harz brought Le Play in close contact with “villages and regions whose ancient customs had not yet been disrupted by modern life.” Le Play, you write, “escaped the modern metropolis for the towns and villages of distant lands … to recover a sense of the more integrated community, where patrons had close contact with working people and knew them individually.” For his budget studies, close observation of family life was a prerequisite. A side-effect was that Le Play and his co-workers thus automatically conferred “respect” to “traditional structures of society.” You go on to explain that Le Play had a keen eye for the sufferings of the common man, but hoped to reform modern social relations in harmony with traditional social ties.

In a recent presentation for the history of science and technology seminar in Suisse Romande, Sophie Cras explained how Le Play brought his intimate and involved mode of observing to the public at large at the universal exhibitions in Paris. After the first exhibition had opened its doors in 1855, Le Play managed to add a separate pavilion dedicated to socio-economics, in which the public could see with its own eyes industrialized versions of the traditional bonds between patron and workman. Engravings of the exhibition of 1867 at the Champs de Mars for which Le Play was the general commissioner, show the Paris bourgeoisie parading in front of ‘small industries’ such as the hat-manufactory of the Brothers Haas and along displays of a separate section devoted to household products (see Figures 1 and 2).

Figure 1. Jules Blanadet, The little crafts – Mr. Haas’ felt hat factory. Source: L'Exposition Universelle de 1867 Illustrée, 1867. Wikimedia Commons.

Both engravings bear witness of the fact that Le Play aimed to observe the life of ordinary workmen with the aim of social transformations that were not in conflict, but in harmony with an expanding industrialized and commercializing world. Even though hat-manufactories such as Haas (Fig 1) were among the filthiest of the time, the display suppressed all the dirt and exploitation, and pictured social ties to be as decent and moral as Le Play wished them to be. Le Play’s display of consumer products in Figure 2 was much discussed in the press because of his innovation of putting price labels next to the objects (small white rectangles in Fig. 2), thus forging direct links between the homely sphere of the family and commercial consumer markets. Le Play thus invited the public to walk along the household supplies as if they were at Lafayette. Adding prices to the supplies, made the commodification of the household appear as a neutral matter.

Figure 2. Jacques Desroches-Valnay, Class 91, Household goods – Low-cost products. Source: L'Exposition Universelle de 1867 Illustrée, 1867, p. 117.

The presentation by Sophie Cras made me rethink the tension you draw between the flaneur and Le Play as a reflection of your own method of observing. You taught us to understand numbers as political, and I take it that your characterization of the observations of flaneur and census taker as “neutral and detached” is ironical. After all, the very presence of the flaneur in the arcades was an expression of his critical attitude towards a society that was increasingly governed by a utilitarian moral and a productive system in which time was money. In contrast, by looking closely, Le Play explored the possibilities of a moral order that would preserve the merits of the old within the promises of the new.

Am I wrong in thinking that your own method of observing combines the best of both? Le Play may have learned to observe sagely, but he lacked the critique of the flaneur. Your method of observing a numbered culture breathes critique from beginning to end combined with a deep respect for the historical actors. And as you explained to me, its basic structure consists in strolling around and finding things out.

With friendship,



1. Theodore M. Porter, ’Reforming Vision: The Engineer Le Play Learns to Observe Society Sagely,’ in Histories of Reforming Vision, Lorraine Daston and Elizabeth Lunbeck, eds. (Chicago: University of Chicago Press, 2011), 281–302.

University of Lausanne


Ted’s numbers have accompanied me my entire academic life. I first encountered his Trust in Numbers when I was an undergraduate student in the Faculty of Sociology at Bielefeld University. Trust in Numbers made me curious and want to learn more about numbers and calculative practices. It played a major role in luring me into the study of bookkeeping, financial reporting and auditing, and in my decision to embark on an academic career in that field. The book has been a faithful companion ever since: it accompanied me during my doctoral studies at the LSE, and it has continued to be a rich, invaluable source of inspiration for me until today. Ted’s Trust in Numbers is core reading in the doctoral course I teach. It is also more broadly a must-read for all students interested in the critical study of accounting.

Ted’s Trust in Numbers taught me the importance of paying attention to the mundane and plain. It helped me understand the multifaceted roles of quantification in animating and sustaining political and economic orders, be it Western dreams of democracy, Soviet imaginaries of planning, or post-Soviet ideals of market-oriented control, which I came to study. It made me see and scrutinize links between quantitative methods and administrative routines. It made me question the often presumed functionality of accounting numbers, appreciate their institutional and cultural conditionality, as well as ambivalence, weakness and vulnerability.

What does it take to make numbers valid? How do numbers gain power? Wherein consists their appeal? These are some of the questions that Ted posed, and that he inspired me to pursue further. First, in the study of credit lending practices of post-Soviet Russian banks; then, in investigations of post-Soviet audit practices and attempts to bring these into harmony with international standards; and, more recently, in examinations of performance measurement, rankings and ratings in universities, hospitals and prisons.

Ted’s works on numbers, which paralleled the emergence of the now firmly established field of social and institutional studies of accounting (see here also Anthony Hopwood’s, Peter Miller’s and Mike Power’s works), drew my attention to how numbers are involved in the construction of social order. As Ted put it, numbers create new things and transform the meanings of old ones. They are “technologies of distance.” As Ted has so vividly shown, numbers make knowledge impersonal. They separate knowledge from its local context and, thereby, help it travel and overcome distance. Yet, the objectivity often attached to numbers is not an inherent quality of them. Such objectivity is not given, but the effect of human regulation, organization and discipline; in short, a collective product and administrative achievement. Also, the credibility of numbers is not merely a technical, but equally a social and moral problem. These insights helped me see the roles of numbers in credit lending processes, which I studied in the 1990s in post-Soviet Russia, in a different light and query the conditions for trust in numbers. Inspired by Ted’s works, I investigated trust as an essential social mechanism which, on the one hand, supports the functioning of accounting systems by bridging their uncertainty and explanatory deficits. On the other hand, the maintenance and successful working of trust in numbers presuppose institutionalized distrust in the form of a complex network of expert systems, sanctioning mechanisms, and other supervising structures, guiding the choice to trust. Using the negative case of the Russian credit economy, where in the 1990s institutional trust was a rare resource and the institutional guardians of trust missing, I examined the multi-layered dynamics between trust and its control mechanisms.

Many years later, in 2009, I had the pleasure to encounter Ted for the first time in person at the Interdisciplinary Perspectives on Accounting conference in Innsbruck, to which he had been invited as a keynote speaker. In 2014, I was delighted to be given the opportunity to interact with Ted again at the Wissenschaftskolleg zu Berlin, where we were both part of the Quantification Focus Group led by Wendy Espeland. In our weekly meetings we discussed our work in progress. We engaged in close reading of each other’s works and explored the production and uses of numbers in different institutional and historical contexts. Here, I learned more about Ted’s enthralling work on asylum statistics and human heredity in asylums, later published by Princeton University Press as Genetics in the Madhouse: The Unknown History of Human Heredity. I had also the privilege to experience Ted’s unique sense of humour, his wit, modesty and collegial generosity.

At the Wissenschaftskolleg, I was also introduced to Ted’s ‘Funny Numbers.’ Taking struggles over cure rate measures in nineteenth-century asylums as an exemplary case, Ted showed how cunning backstage manipulations can make numbers ‘funny’ in the sense of becoming deceitful whilst maintaining a boring, technical appearance. Such ‘funniness’ can make numbers also dangerous. For it is their very ‘coldness,’ their apparent objectivity, which, on the one hand, is so cherished by those who trumpet their virtues, yet, on the other hand, is also very fragile, easily corrupted and turned towards other goals. As Ted points out, such dangers are also evident in recent efforts of governments and corporations to decentralize their functions using incentives based on quantified targets. Exposing the funniness of numbers, Ted is not only a brilliant historian, but also an important critical public voice contributing to the campaign for the responsible use of metrics in research, education and beyond.

Ted’s numbers will always stay with me. Ted’s multifaceted oeuvre has and will inspire me, for many years to come.

London School of Economics

Martine MespouletSOLVING A RIDDLE

I met Ted for the first time in 2002, during the first conference organized in France on the sociology of quantification, at HEC Paris. Ted had been invited to give a lecture on the sociology of statistics. Since then, we have met on several occasions at conferences and workshops. I have a special memory of his two visits to Nantes. The second time, in January 2014, he participated in the first workshop of a seminar on quantification organized jointly by the Nantes IAS and the one in Berlin. A second workshop took place in Berlin in April 2014. These two meetings gave us more time to discuss my research work on the history of statistics in Russia and the Soviet Union.

In Ted’s eyes, the Soviet Union illustrated particularly the fact that the intellectual and social role of quantification is intertwined as much in production and administration as in science. The way in which sampling methods for the first sampling surveys were produced in Russia before 1917, and then in the Soviet Union, was the outcome of this imbrication. He asked me a question that prompted me to take my analysis further.

I had highlighted a fact that intrigued him as much as it did me: in a handbook of statistics published in 1924 in Saratov, a city in the Middle Volga, Aleksandr. G. Kovalevskii had formulated a mathematical treatment of the theory of stratified sampling which led to a result similar to that set out by Neyman ten years later in 1934.1 Was it just a coincidence? Kovalevskii and Neyman lived more than 1000 kilometers apart, the first in Russia, the second in Ukraine. Did these two men know each other?

I decided to try to solve this riddle! After working on various archival sources, I think I can conclude that this was likely a parallel innovation process, fed from the same theoretical sources.

Born in 1892, Kovalevskii was trained in theoretical statistics at the Law School of Kazan University. A.A. Ovtchinnikov, A.A. Chuprov’s close friend, taught there the application of probability theory to the processing of statistical data. In 1916 Kovalevskii became a statistician in the cooperative movement in Saratov. In 1921 he was appointed by the regional office of the Soviet Central Direction of Statistics. From January 1930 until his death in October 1933, he combined his activities as head of a department of the Bureau of Statistics with that of professor of statistics at the university and then at the Institute of Economics and Planning in Saratov.

Thus Kovalevskii had a dual career, in mathematical theoretical statistics and in administrative statistics. It is not surprising, therefore, that his treatment of stratified sampling has answered practical questions relating to sampling procedures usable in particular in agricultural surveys. In his handbook he mentions that he studied the applications of probability theory to the construction of the sample of a sampling survey on the basis particularly of the work of Markov, Chuprov, and Kon.

Born in 1894, Jerzy Neyman followed a completely different route. From 1912 to 1917 he studied mathematics at Kharkov University. In the summer of 1921, at the end of the Civil war, he went to Bydgoszcz, in Poland, where he held a position as assistant in statistics at the National Agricultural Institute. The research he carried out there for his doctoral thesis, defended in 1924, led him to formulate the method of optimal allocation for stratification in 1934 in an article published in the Journal of the Royal Statistical Society.2 The writing of this text was also the outcome of the experience accumulated during his years of collaboration with Egon Pearson.

Despite their different routes, Kovalevskii and Neyman had in common a similar training in probability calculation, which was characterized by a very good knowledge of Chuprov’s work on probability, especially of his key article published in 1909. In his biographical notice about him, Eugene Seneta points out that a 1923 article by Chuprov published in Metron contained results that could be applied to the theory of sampling surveys and anticipated several subsequent results published by J. Neyman, in particular the formula for optimal allocation.3

The key to the riddle raised by Ted thus lies in the application, at two different times and in two different places, of Chuprov’s theoretical thinking to the resolution of methodological questions linked to carrying out sampling surveys in agriculture in Russia and Poland.

These two parallel innovation processes are likely the outcome of two experiences fed from the same sources, although the trajectories were distinct. The proximity of the theoretical thinking of the two statisticians can be explained by the influence of the legacy of the Russian school of probability. The relationship between administrative statistics and scientific innovation, which is at work here, confirms the importance that Ted brings to it in the production of quantification.


1. A. G. Kovalevskii, Osnovy teorii vyborochnogo metoda, Saratov, 1924, p. 82.

2. J. Neyman, ‘On two different aspects of the representative method: the method of stratified sampling and the method of purposive selection (with discussion),’ Journal of the Royal Statistical Society, 97, 1934, pp. 558-625.

3. C. C. Heyde, E. Seneta (eds), Statisticians of the Centuries, New York, Springer-Verlag, 2001, pp. 303-307.

Université de Nantes


Ted visited us in April 1990, as the Arthur Anderson Visiting Professor of Accounting at the London School of Economics & Political Science. He presented then a draft of his paper ‘Quantification and the Accounting Ideal in Science,’ which was to appear in print a couple of years later. On more than one occasion, and with his characteristic smile, he remarked subsequently that this was the appointment of which he was most proud. At that time, Trust in Numbers was still five years away from publication. But Ted’s passion for analyzing and documenting the quest for objectivity through quantification was already apparent. And his affinity with those of us working on and at the margins of accounting was clear.

Over the coming years, Ted’s writings were to become a mandatory reference point for researchers in and around accounting. He provided an immense boost to our discipline, at a time when the historical and sociological analysis of accounting was in its relative infancy. At times it had felt that accounting was only of interest to accountants, and to those who thought that the main effect of accounting and accountants was to ‘cook the books.’ But Ted showed, as we ourselves already believed, that accounting did much more than that. He showed that accounting was a fundamental component in a vast calculative infrastructure, one that linked with and overlapped with many other forms of quantification.

Ted was to become a consummate human mediating machine for the domain that he in large part created, perhaps exemplified most vividly by the collection he co-edited with Dorothy Ross as volume seven of the Cambridge History of Science. That collection emanated in part from a remarkable symposium held at the Wilson Center in Washington DC in May 1997, in which I was fortunate to be invited to participate. By that point, and through such events and others that Ted facilitated, the historical analysis of accounting and related forms of quantification came to be viewed as a legitimate domain of social scientific enquiry. In time, the human mediating machine became a multiplying machine, as illustrated for instance by The New Politics of Numbers, a recent collection edited by Andrea Mennicken and Robert Salais. I very much doubt that Ted set out to create an entire field of historical enquiry, namely the historical and social studies of quantification. But that is indeed what he has achieved, and in a remarkably short span of time.

One of the charms of Ted’s writings is his ability to analyze events or moments that are pivotal in the emergence of modes of quantifying that are also modes of governing, even though he did not explicitly deploy such terminology. Ted has always told the big picture, albeit through events that are on a somewhat smaller scale than things like capitalism or power. Relatedly, he has avoided fruitless theoretical squabbles, preferring instead to deepen and extend his enquiries into new yet related events, as he has been continuing to do very recently. It is difficult to envisage Ted retiring. It feels as if it was only yesterday that we first met.

London School of Economics & Political Science


Ted and I have a shared history going back to 1982. We were the two most junior members of a fantastic research group assembled for a year (at the ZiF in Bielefeld) in order to study ‘The Probabilistic Revolution.’ This group of scholars, mainly from history and philosophy of sciences, created a life-long series of friendships and have pursued intersecting and parallel projects over these past decades. From that moment of meeting in 1982, I have always looked up to Ted, not only because he is taller than me, and was a year ahead of me (he had finished his PhD and I was still doing mine, and like siblings that gap does not quite go away), but because Ted is a proper historian whose love of the archive remains alive in his books whereas my archive commitment has dissipated over the years. During Ted’s research trips to London, we would start each evening with his latest archive find, and end with convivial sociability or concert going.

The most significant outward sign of my profound respect for Ted is that his ideas about the role of numbers in society have become a key element in my teaching. I introduce my students to Ted’s work in week 2 of my graduate course on how economists’ ideas have changed the world. This is not an intellectual history course, far from it; rather it is a course on ‘performativity’ or how economic ideas about how an economy could or should be organised have been put into practice to shape or change the way a national economy works. Students start from some historical case studies of radical changes in economic arrangements: for example, how economies get reconstructed after a war, how economies get changed from capitalist to socialist or vice versa, how newly independent African economies get remade after colonialism, and so forth. The puzzle is, how do these major changes happen? For me, this is a question that focuses attention not on socio-economic policy (as if simply stating a policy is all that is needed), but on the processes, people, and their agencies in making economic change happen. Ted’s work provides an essential framing argument in the course.

I begin my teaching with Ted’s Trust in Numbers (1995), and his ideas about why and how members of society gain trust in certain kinds of administrative, economic and social scientific numbers; and of course those categories overlap. As I understand and portray his argument, there are two elements that contribute to this perception of trustiness. One is SQR’s—the fact that the kind of numbers used by social scientists are the result of Standard Quantitative Rules of measurement of the phenomena of the socio-economic world, often collected by and for ‘the state.’ The second is that these numbers are collected by institutions that have professional expertise in conducting such measurements, and that have some distance from the centre of government, and that take pride in their active bureaucracy. Trust is gained in the quality of numbers not only because users trust in those who collect those numbers but also because of the stability of their design and rules of collection. Together these validate the notion of such socio-economic numbers taken by users to be ‘objective.’ This quality is a social acquisition, not a philosophical judgement.

But this is only half the argument for me. The second half is found in his lovely paper of the same period, ‘Making things Quantitative’ from 1994 (Science in Context) which takes another important step. His opening states the ambitious agenda: “Quantification is not merely a strategy for describing the social and natural worlds, but a means of reconfiguring them.” He observes that measurement in the natural sciences often takes place even where there is a lack of clarity over the phenomena, or even specific disagreement about the causes of variability in the natural object (as in Hasok Chang’s history of the thermometer). Despite these problems, a trusted measurement instrument, and system, may be established and remain stable. The next step of his argument is critical: as measuring instruments, his SQRs are as fertile as experiments and instruments in the natural sciences at defining new things in the social world. Thus, SQRs do that same kind of work in the social domain as physical measuring instruments in the natural space. The implication that SQRs create long-lasting conceptual materials for the social sciences is, I think, completely convincing. How else could we have obtained belief in the CPI (consumer price index) or the GNP (gross national product) as ontic furniture of our modern economic world (from around 1900 and 1950 respectively)? Those labels are labels of measuring systems at the same time as labels of things we treat as existing in our economic world and have some experiential engagement with: namely, inflation and national income. Economists may disagree about the causes of inflation, and argue about its measurement, but only about different variations within the basic index-number definitional framework. Economists may believe that GNP is not a very accurate measure of national income, and its scope is indeed very gradually changing as the nature of income changes. But, as ontic furniture, they are not in doubt. This joins the ideas from Ted’s ‘Making things Quantitative’ to one of my favourite philosophers of science, Nelson Goodman’s, philosophical tract Ways of Worldmaking (ways that are shared between the science and arts).

The final insight from Ted’s analysis links the ontic furniture to the social technology that is created around them. This is where his promised ‘reconfiguring of the social world’ takes my class to the issues of agency in the work of my favourite sociology of accounting folks: Mike Power and Peter Miller, who show us how individuals act on numbers and their categories to make their organisations work. Inflation and GNP are not just ontic furniture, they are dynamic elements in the economy. As inflation goes up and down, people’s behaviour adjusts, changes, and so affects inflation and its numbers. The GNP numbers are not just used in reasoning by the state for policy decisions; those aggregate numbers are made up from categories of everyday action in the economy: decisions on investment, consumption, saving and so forth. Those individual actions change the GNP numbers. People act on their economic experience, and economic numbers provide the information for acting upon, so these SSQ measurements and their associated concepts are elements in a broad social technology in which the numbers and the activities are co-active and co-determined. These are not the closely related actions of a smaller set of individuals studied by Donald MacKenzie to demonstrate performativity in a particular financial market. Rather, the ‘social’ here marks the vast but unknown social connections of economic activity via a technology of measurement systems producing SQRs. Making things quantitative sets off a social technology that changes the economic world: maybe from capitalist to socialist, maybe from socialist to capitalist, but essential in both such major shifts. Thank you, Ted, for showing me how the use of numbers holds the key to how economies change their spots.

London School of Economics

Christine von OertzenPAULINE’S PETITION

On New Year’s Day in 1888, Countess Pauline von Bismarck posted a petitionary letter on black-rimmed mourning paper to the Prussian ministry of the interior.1 The young countess had recently lost her much older husband Busso, a presiding judge at the Higher Regional Court in Breslau (today the Polish city of Wrocław) and member of the Prussian state parliament. Despite his public and social standing, Busso von Bismarck had left his wife with precious little to live on. Pauline was in dire need of a way to make ends meet. On behalf of the custodian of her children (another sprout of the mighty von Bismarck clan), Pauline introduced herself to the director of the Prussian statistical bureau. Given her difficult circumstances, might she be granted permission to take on statistical work to supplement her meager allowance? Because of her name, she reasoned, no other form of employment was available to her. Pauline von Bismarck required additional income shielded from public attention. And the Prussian statistical bureau provided it: from August 1888 onward, the young countess was listed as a houseworker for statistical work. Boxes with census records were delivered to the widow’s apartment in Berlin-Schöneberg, located about three miles southwest of the bureau. Records show she earned 140 reichsmarks for her data compiling efforts in 1889.2

Pauline von Bismarck’s discreet arrangement with the Prussian census bureau appears to offer a curious anecdote of Prussian autocratic favoritism. In fact, the countess was far from the only woman in Berlin sorting and counting census data from home. What made Pauline’s case exceptional was her aristocratic background: most of the young widow’s at-home counterparts were from the middle classes. Unlike von Bismarck, these women shared some kind of kinship relation to men hired by the bureau (and were thus encouraged to spare their parlors for sorting and counting census information). As at-home compilers of the state’s census statistics, these women constituted an integral part of a larger story on bureaucratic paper technologies, knowledge practices, and gender politics. Their labors underpinned increasingly complex operations of the Prussian state government, first and foremost in census taking, and this in an era when the processing of numerical data was becoming essential.

Pauline’s petition could be granted owing to a special paper form: the Prussian census card. Known in German as the Individualzählkarte, this mobile data carrier had been introduced as a key component of Prussia’s ambitious census reform two decades earlier. It replaced enumeration lists for gathering information. Its overarching aim: to ground statistics in a flawless operation of collecting and compiling information gathered at each door by following a strictly centralized protocol. Cherished among Prussian statisticians as a precision tool superior to the American Hollerith punch card introduced at the dawn of the twentieth century, counting cards long served as Prussia’s data gold standard. The Zählkarte built confidence in the authority of what Ted has called tabular reason: the establishment of a data-driven spirit, a bureaucratic mode of knowledge-making that fashioned large aggregates and correlations out of the untidy business of societies’ doings and dealings.

Pauline’s—and many other homebound women’s—involvement in compiling aggregates sheds light on the conceptual and logistical efforts behind tabular reasoning. Counting cards were lauded as cutting-edge enumeration tools. At the same time, the Zählkarte dictated a highly idiosyncratic system of processing the gathered information. Designed to enable a seamless process from inscription to tabulation with as little human interference as possible, the cards actually ended up going through many hands at many different places while being sorted and counted, crossing boundaries among the experts of the statistical bureau, as well as hundreds of different homes scattered across, and well beyond, Berlin.

Following the counting cards on their far-flung journey enabled me to explore worlds of tedious bureaucratic planning, abrupt improvisation, social aspiration and distress, housewifery orderliness, and cognitive endurance. Taken together, they made the unruly Prussian system of creating numbers work. And how fortunate I have been that Ted shared my enthusiasm for this undertaking!


1. Pauline von Bismarck to Emil Blenk, 1 January 1888, Preußisches Geheimes Staatsarchiv (GhStA), I HA, Rep. 77, Tit. 536, no 30, vol. 1, n. p.

2. Register of all ancillary workers employed on April 1, 1890, Verzeichnis sämmtlicher Hilfsarbeiter nach dem Stand vom 1. April 1890, GhStA, I HA, Rep. 77, Tit. 536, no 30, vol. 1, n. p.

Max-Planck-Institut für Wissenschaftsgeschichte, Berlin

Jahnavi PhalkeyALL BECAUSE OF TED!

Quantification has not yet become a topic in political philosophy. Not that its political dimension has been ignored. An abundance of seemingly contradictory views have been advanced by moralists, critics, and quantitative researchers themselves. This corpus of writings includes some ill-considered polemics, but also some nuanced and thoughtful discussion. The best arguments are by no means all on one side. Unfortunately, there has been little dialogue. Critics, especially on the left, present the quantitative mentality as morally indefensible, an obstacle to utopia. Trust in Numbers p.73

“Quantification has not yet become a topic in political philosophy.” I read this sentence in chapter four of Ted’s Trust in Numbers: The Pursuit of Objectivity in Science and Public Life and put the book down only to pick it up and read it all over again—mesmerised. I was then a new graduate student who had come to history of science with degrees in civics and politics. It was the same year that I picked up Shapin and Schaffer’s Leviathan and the Air-pump: Hobbes, Boyle, and the Experimental Life, and was completely blown to find out that Thomas Hobbes of “solitary, poor, nasty, brutish, and short” fame was interested in the study of motion and physical momentum, and that he scorned experimental work! It was like finding the key to a locked room at the back of my own house—and it led to an ocean that I had not known before. Had I found the archive early enough, I might have written a dissertation and then (hopefully) a book about numbers and their public life in mid-twentieth century India. Instead, I wrote about the beginnings of experimental nuclear physics.

“The credibility of numbers, or indeed of knowledge in any form, is a social and moral problem,” Ted says elsewhere in the same book. When administrative power and technical knowledge became inextricably intertwined at the end of WWII, this was true for both experimental nuclear physics and for the production of seemingly reliable numbers. In India, the production of scientific and technical knowledge, at least in the disciplines that I study, became a statist-bureaucratic-procedural exercise. In one fell swoop, an exercise in standardising categories of measurement across the swathe of land now called India was implemented and in doing so particularities of the tenuous new multi-nation state that emerged in the middle decades of the twentieth century were erased.

At the end of my epigraph, Ted observes that “critics … present the quantitative mentality as morally indefensible, an obstacle to utopia.” As recent publications by Poornima Paidipaty and Nikhil Menon have shown us, numbers, accompanied by planning, in fact promised and described nothing less than a utopia for citizens of the newly independent country. How they did this—generate the categories, produce the numbers, and present an argument for an idea of India—and how it met with mixed success and an eventual decline is an interesting story that has already run full cycle.

It takes an enormous exercise of social and political power to establish the validity of numbers as true claims. And at some point, I was fascinated by one aspect of this story—national income accounting, the exploration of which led into what was to me the unfamiliar territory of late nineteenth-century India. Around the time that the statistical argument for India’s freedom appeared interesting to me, I was privileged to spend ten months with Ted and six other scholars who thought seriously about numbers at the Wissenschaftskolleg zu Berlin. While I had met Ted very briefly in Los Angeles about five years before that, this was the first time that I interacted with him almost daily in close proximity. We met as scholars in residence, as members of the Quantification Group, and in a German language class. Ted was the most inspiringly disciplined of all of us in no matter what he did, including attending the opera, and he had the best sense of humour. It was mesmerising to listen to him elocute passionately about asylum records and about heredity. He loved his archival documents, his work, and his life. He had a gentle presence, a kindness one can only hope for among colleagues, and he cared deeply about the few of us around him in an unassuming practical way—he was interested in us as fellow beings and in our ideas (of which I had unfortunately very few at the time). Around Ted, there is no drama.

Jahnavi Phalkey, Ted Porter, and John Carson at the Wissenschaftkolleg zu Berlin.

It is from Ted’s work, and later with him, that I learned to ever more deeply appreciate numbers and their public life. After I left Berlin, I continued to dig deeper into the archive. In my later conversations especially with the historian of China, Arunabh Ghosh, who also draws on Ted’s work, I have—finally, very likely—found the slab of marble from which to craft a story. All going well, I will write the biography of D2 or Malahanobis Distance, “an effective multivariate distance metric that measures the distance between a point and a distribution.” Prasanta Mahalanobis, physicist turned statistician, proposed this sampling method in 1936, which then became foundational to the production of useful numbers in free India and beyond.

Numbers have been Ted’s friends for most of his career. He has found numerous ways to reveal their social-political lives, understand them, and speak of them. I took from him a little bit of that fascination with me when I left Berlin (and I left intact with him all the fascination he had for Norway). My own writing remains in suspended animation. This time, it is not because of a missing or inaccessible archive. I have made choices that have made it difficult for me to find the time to write. When I do write that book about a sampling technique developed in India—and I hope that will be rather soon—it will be for Ted.

Science Gallery Bengaluru


We are in 1910 France. In the press and in Parliament, social struggles converge around the preparation of the law on workers’ and farmers’ pensions. This would be the first real social insurance, in the sense that it would be financeed by contributions from employers and employees, supplemented by state funding. In the Senate, driven by its “shrivelled, miserable, wrinkled, aged wisdom,” the industrialist Eugène Touron organizes the resistance with “the determination of the Sioux trampling on the corpse of his enemy."

But on the other side of the fence, the workers’ militants are not all enthusiastic. The age proposed for the right to a pension, 65 years, is judged too high for the pension to be anything other than a forfeit. The Confédération Générale du Travail (CGT), the main trade union, denounces the “retirement for the dead.” For Paul Lafargue (1842-1911), Marx’s son-in-law, the new system would be nothing more than a tontine: workers surviving to the required age would receive a pension fed by the contributions of their comrades who died before reaping the fruit. A third source of anger materialized around the stamps that employees will have to stick, throughout their cursus laboris, on a booklet they will require to receive their pension. For French workers, many of whom are close to the skills, work organization and ethos of independent craftsmen and to Proudhon-style anarchism, the proposed regime means accepting the subordinate relationship of salaried employment for life—a relationship which the CGT is fighting to abolish.

It is in this context that Jaurès intervenes. The future martyr of the cause of peace (he will be assassinated by a nationalist militant at the outbreak of the First World War); co-founder of the French socialist party, the SFIO; director of the newspaper L'Humanité; great rhetorician and intellectual (a graduate of the Ecole Normale Supérieure, he authored a monumental Histoire Socialiste de la Révolution Française); he tries to enlist the socialists and trade unionists in support of the bill through his interventions in the party newspaper and in the Chamber.

His precision of thought, his rationalism mixed with iconoclasm, his faith in social and political justice, but above all his ‘trust in numbers,’ reminded me of the many discussions, both scholarly and political, that I have had with Ted. I will present some of them here, hoping that they will make him smile, in the first or second degree...

The tribune is not soft on the labor movement. He denounces its inconsistency, its “phantasmagoria,” its “childish squabbles,” its “ineffectual little sulks,” its “chimerical and childish fears,” its “mad panics,” and particularly castigates the theatricality tinged with masochism of those who “play at destroying their booklet” or prophesy the “fearsome inquisition” of a “bureaucratic police regime.” Wanting to shake up “the most indifferent, the most overwhelmed, the most inert, those who oppose to every new idea and every formula of progress an impenetrable ignorance or a thick skepticism,” Jaurès laments the:

misfortune of the French working class, namely its mediocre preparation for positive questions, and management of its material interests. It has great political traditions. It has a strong sense of democracy, a taste for general formulas. It knows how to be passionate about large objects; but is not prepared to understand and handle great social institutions; and as it knows little about these things, it has, in these matters, the mistrust of the weak.

To the moral indignation against the age criterion retained by the law, Jaurès opposes the security offered by the insurance principle. In contrast to assistance, which “submits the right of individuals to arbitrary interpretations [...], insurance creates an absolute, unconditional, indisputable right, realized with mathematical and automatic certainty.” But how to appease the workers’ fear that the state, “a mysterious and formidable bureaucrat, will steal their savings"? This is where trust in numbers comes in. If we can count on insurance rights defined by mathematical neutrality, it is because historical experience proves that all the institutions and forms of savings created by France over the past century have proved reliable.

"The pension will be due to the workers, as is due to the holder of a title of the French State the annuity of this title.” HE goes on:

There is one thing that is irreproachable in bourgeois society, in bourgeois governments: it is administrative accounting [...]. Not a penny goes astray. The slightest state bankruptcy is impossible, and the pension funds, handed over to the Caisse des Dépôts et Consignations (CDC), subject to the State control of the Inspectorate of Finance and the Court of Auditors, placed in secure values and managed by commissions including the workers themselves, are as safe from any risk as the funds of large, medium and small French rentiers. Savings bank funds are already reaching a figure of billions that capitalized pension funds will only reach in many years.

This national system of mutualized savings, based on the creation of the CDC and national savings banks in the 1810s, and of the National Pension Fund for Old Age in 1850, came to materialize the aspirations of the Enlightenment, synthesized by Condorcet at the end of the eighteenth century. But where does its reliability and trustworthiness come from?

If “the credit of savings banks is of unshakable solidity,” if “government securities constitute the strongest investment in the world,” it is because “if the State committed the folly of touching these deposits, it would see the five million depositors rise up against it like a formidable army.” The notion of accountability, the foundation of democracy, finds here its most material illustration. Ultimately, for the socialist Jaurès, a man of the Enlightenment, it is the democracy of savers that ensures trust in numbers.


All quotations are taken from Jean Jaurès’ speeches in 1910 in the Chamber of Deputies and in the socialist daily L'Humanité. They have been republished in volume 14 of his Œuvres (Paris, Fayard, 2022), by Marion Fontaine, Alain Chatriot et al.

Centre d’Histoire de Sciences Po


Since reading Ted’s seminal accounts of ‘mechanical objectivity’ and ‘thin description,’ my attention to quantification, and more broadly to technicization, has been shaped by its inherent antinomy. Ted has shown us that we are dealing with an intractable epistemological problem. I want to continue to support the open agenda he has started for the social studies of quantification. Today I offer a reading report that reminds us of a fascinating ancestor of our agenda, who framed it as the question of how to hold Leistung (efficiency) and Einsicht (insight) together.

About ten years ago, more or less by accident, I came across some writings on technology by the philosopher Hans Blumenberg. I could not stop rubbing my eyes. Here I would like to recall my inexplicably delayed reading of Blumenberg’s writings on technology and in particular his seminal essay Lebenswelt und Technisierung unter Aspekten der Phänomenologie (Blumenberg 1963). Blumenberg provides a critical summary of one of Husserl’s core arguments (Husserl [1934-37/1954] 1970). For Husserl, technicization is the “transformation of a formation of meaning which was originally vital into method, which then can be passed on without carrying along the meaning of [its] primal establishment” (cited in Blumenberg [1963] 2020, 381).

Blumenberg places Husserl’s fear that technicization makes us “take for true being what is actually a method” (Blumenberg [1963] 2020, 382) at the center of his broad investigation. He argues contra Husserl that if the lifeworld is about routinization and if technicization is its most effective form, then the core function of technicization is to provide Sinnverzicht (suspension of meaning) (Blumenberg [1963] 2020, 391). Technicized routinization relieves us of the burden of pondering the full meaning of what we are actually doing when we engage in a routine praxis such as deploying a scientific method, operating a machine, or running everyday errands. Put differently, suspension or renunciation or deferral of meaning making is a necessary element of technicization for one cannot and does not want to start from scratch in each attempt to solve a problem.

In making this point, Blumenberg does not question Husserl’s diagnosis that technicization also causes Sinnverlust (loss of meaning) (Blumenberg [1963] 2020, 381). In Husserl’s perspective, technicization refers to the replacement of fundamental sensemaking by unsuspicious and methodological rule-following practices that allow one to keep going, untroubled by questions for which one has no answers. In this view, questions like ‘What is it that we are doing here?’ or ‘What is it that we have in front of us?’ are lost through technicization. Blumenberg objects by maintaining that we are here dealing with an antinomy: technicization cannot produce Sinnverzicht without at the same time causing Sinnverlust, yet Sinnverlust through method is the presupposition of new Sinnbildung—to construct new meanings.

Technicization means to be able to learn the skill of “doing a thing without having to understand the thing itself and tying back the necessity of its execution to the essence of that thing” (Blumenberg [1963] 2020, 364). This distinguishes technical knowing-how from the theoretical-scientific relation toward the object as knowing-what. A decrease in Einsicht (insight) is traded for an increase in Leistung (efficiency). For Blumenberg, this trade always begins with what he calls Urstiftungssinn (original insight), but even this original insight is not lost through technicization but kept as Sinnsedimentierung (sedimentation of insight) in a technological archive from where it can be retrieved.

As long as technicization runs smoothly for all concerned, it becomes normalized and unquestioned mundane routine. The inevitable arbitrariness, contingency, and lack of certainty disappear in the hinterland. Once the efficiency and plausibility of this thinning process are disrupted, the uncertainty of the foundations of the original insight and its translation into method are exposed. The deferral of fundamental sensemaking through technicization and its occasional disruption hence constitute each other as the two indispensable sides of the same practice.

Some of us are currently involved in debates about ‘data deluge.’ Part of this debate are questions concerning one of the most fascinating and frightening Golems of our time—Artificial Intelligence (AI) with its learning algorithms and with ChatGPT as its presently most popular form. Its hair-raising fascination is triggered by the old question of human responsibility for technicization, which Blumenberg reiterates (Blumenberg [1963] 2020, 372). Following Blumenberg to support what we are doing in Ted’s footsteps, we can say that artificial intelligence is the quintessential expression of technicization, which works precisely because it so effectively achieves the intended Sinnverzicht. It cannot do this without causing Sinnverlust. But in doing so, it invites us to ask for a new Urstiftungssinn and thus to initiate a new cycle of Sinnbildung.

And indeed, as AI becomes more popular, it becomes more apparent that one of its characteristics is indeed its lack of intelligence. It cannot operate other than on the basis of Sinnverzicht. Another key characteristic of AI in the version of ChatGPT and similar deep learning machines is also a consequence of the same Sinnverzicht. It can only work if it also renounces any moral stance. Noam Chomsky aptly observes that ChatGPT doesn’t take a position on anything, and when pressed by human users, openly admits that it is “just following orders.” In order to work, a learning algorithm must be unintelligent.

We have no reason to expect in the near future that AI will offer us a new Urstiftungssinn, any more than we have reason to trust human prophets who tell us that AI is the work of the devil. Instead, we trust Ted and continue our exercises with openness.


Blumenberg, Hans. 1963. ‘Lebenswelt und Technisierung unter Aspekten der Phänomenologie.’ Filosofia 14 (4): 855-84.

Blumenberg, Hans. (1963) 2020. ‘Phenomenological Aspects on Life-World and Technicization.’ In History, Metaphors, Fables: A Hans Blumenberg Reader, edited by Hannes Bajohr, Florian Fuchs and Joe Paul Kroll, 358-99. Ithaca: Cornell University Press.

Husserl, Edmund. (1934-37/1954) 1970. The Crisis of European Sciences and Transcendental Phenomenology: An Introduction to Phenomenological Philosophy. Evanston: Northwestern University Press.

University of the Witwatersrand, Johannesburg


Ted Porter has been a constant friend for most of my career. When I decided to specialize in the history and philosophy of economics, as a doctoral student at the University of Toronto, my professors at the IHPST voiced considerable skepticism about my career prospects. I managed to land on my feet, though not without some stumbles along the way. From an early stage, Ted proved to be one of my closest friends and supporters among historians of science, not least because his work demonstrated so forcefully the value of the history of the social sciences, and the history of economics more specifically. We first met at the International History of Science meetings at UC-Berkeley in the summer of 1986. Ian Hacking, who had examined me on my doctoral thesis, hosted a party in Berkeley for his collaborators on the Probabilistic Revolution project at ZiF, and kindly included me as well.

From that point on, I would run into Ted at least once a year, at one meeting or another. In 1987, at the History of Science Society meetings in Raleigh North Carolina, I had organized and chaired a session on the history of economics, composed of Mary Morgan and two eminent scholars, Roy Weintraub and Neil De Marchi, both at Duke University. Alas, the audience had only one person, namely Ted, but of course he was the ideal attendee. Things improved over time. Thanks to Ted, and many others such as Mary Morgan, Norton Wise and Lorraine Daston, the study of economics gradually became part of mainstream history of science. Each of the aforementioned included me in a number of panels or small workshops that helped me mature as a scholar. If, in subsequent years, I organized a session at the History of Science meetings, Ted more often than not would be one of the speakers. He also frequented the History of Economics Society annual meetings, as well as specific workshops in that field. We shared a common criticism that much of the work in history of economics was hampered by, as Ted aptly put it, the desire for legitimation by mainstream economists.

When I first met Ted, he had just published his wonderful book, The Rise of Statistical Thinking: 1820-1900 (Princeton, 1986). It was also one of the first books that I reviewed, for Victorian Studies. For many years thereafter I assigned it in graduate seminars, and always benefitted from reading it again. Its greatest legacy is bringing to light the complex give and take of the natural and social sciences as statistical thinking took hold. It also helped draw attention to the philosophical work of William Stanley Jevons that was the subject of my first book, A World Ruled by Number (Princeton, 1990). Because it was published with the same press, Ted’s book was given full billing on the back jacket, including a quote from the New York Times praising his work as “unfailingly interesting.” He is also quoted on the back jacket of my second book, The Natural Origins of Economics (2005), no doubt having served as a referee, as I had done for his second book, Trust in Numbers (1995). I don’t believe there is a word to capture the particular relationship of someone popping up more than once on the back jacket of one’s books, but it is a testament to Ted’s inspiration and steady support for my own work, and rightfully gives him the last word.

In keeping with David Lodge’s Small World, I have crossed paths with Ted in numerous cities around the world, both in North America as well as many European cities, London, Paris, Edinburgh, and Berlin, to name just a few. Most memorable was a week-long tour of northern India, in 2007, to celebrate the birthday of his UCLA colleague Peter Baldwin. I have a fond memory of chatting with Ted during our tour of the City Palace in Jaipur which housed an observatory for astrological purposes. I had also come to befriend Mary Terrall, meeting her first in 1992 while I was a visiting professor at CalTech, and before she had risen to stardom with prize-winning books on science in the French Enlightenment. I was so pleased for them both when they joined forces about a decade later, a clear case of the whole proving larger than the sum of the parts.

Ted has a great gift for friendship. He has been unfailingly kind to me, particularly as a single mother. In 1997, I spoke at a small conference at UCLA in preparation for the Cambridge History of the Modern Social Sciences (Volume 7), which he co-edited with Dorothy Ross. Because I had my infant son in tow, Ted arranged a full-time baby sitter, and also took me to the optician when I broke my glasses during the visit. But what most comes to mind is Ted’s gift for listening and for conversation. Whatever I might say, he would ponder it quietly and modestly, issue his characteristic monosyllabic chime, and then invariably respond with a remark both insightful and witty.

Because of the pandemic, our paths have not crossed for several years. The last time I saw him was in April 2019, when he attended a conference in honor of Jed Buchwald’s birthday, held at CalTech. My presentation was about David Hume’s proto-econometrics, which would become a chapter in my next book, co-authored with Carl Wennerlind. Ted was full of praise and expressed interest in reading more about Hume’s economics. In sum, he’s always been gifted at boosting my spirits; now it is my turn to do the same. Ted, you have had a remarkable career, and your work will be admired countless years from now. But above all, you’ve been a great friend. I hope we visit more palaces and museums together, and more birthday celebrations. I wish you many happy years in retirement, hoping you will find new passions and proclivities.

University of British Columbia, Vancouver


I once had the pleasure of delivering a talk at a conference organized by Ted in which I identified my historical sensibility as a combination of Ted Porter and Martin Rudwick. Anybody who knows me will know that Martin has been a guiding influence on my career, so (while intentionally cheeky) this comment offered the highest praise I can give to a historian.

Unlike many of the other contributors to this collection, I probably engaged with Ted’s work a little later in my career, given that I didn’t transition to writing about the modern period until after graduate school (although I do remember Trust in Numbers was on my prelim exam reading list!). I reengaged with Ted’s work around 2011, when I began working on the history of data practices in nineteenth-century natural history and Kameralwissenschaft and I needed some broad guidance about the history of statistics and statistical practices of that era. I devoured The Rise of Statistical Thinking, along with other now-classic studies by scholars like Ian Hacking, Alain Desrosières, Steve Stigler, and others.

For me, Ted’s work spoke the most directly to the kind of project I wanted to do: a careful, detailed analysis of statistical practice in specific disciplinary contexts connected to a larger argument about what those practices reveal about the developing epistemology of modern rationality. Reading Rise was one of those rare experiences where one reads exactly the right book at the right time: Ted instinctively saw that the epistemological politics of statistical thinking was shaped by interactions between bureaucrats, political economists, pure mathematicians, and practitioners of various social and natural sciences. Suddenly, the project I wanted to do—linking bureaucracy to natural history via statistics and statistical visualization—made perfect sense! Looking at the world as data was a deliberate choice made by people in a specific time and place, and had to be established as a valid way of understanding the world—the creation of an epistemic community. And of course rereading Trust helped amplify the social and epistemological functions of this process, with particularly powerful insights into discipline formation.

While I know that some readers (i.e., grad students to whom I’ve assigned the book in seminars or directed readings) feel some exasperation at the dense chapters and case studies in both books, for me those were the exciting parts. Ted is a big thinker with a willingness to stake major claims, but he is also a careful student of practice and an omnivorous consumer of dry statistical analysis. Every historian should have a slogan: I fondly recall another of my intellectual touchstones, Raine Daston, commenting that her approach is to “historicize the self-evident.” I think Ted does this in spades, but my vote for his personal motto would be “making the dull exciting”!

What I was getting at when I opened that talk with the juxtaposition of Ted and Martin was that both authors have a fondness for longue durée histories that recover practices formative to the construction of entire worldviews with verve, wit, and exhaustive knowledge of sources most of us would overlook. Putting the two in conversation has been immensely generative for my own work: the ‘discovery’ of deep historicity in nature relied on new techniques for narrativizing deep time (the analysis of large quantities of numerical data) and a new epistemology for making meaning from those statistical abstractions (trust in numbers). If I’ve done nothing more than expand a small portion of each of those historians’ works, I’m completely satisfied.

In the process—and thanks to overlapping periods spent in Berlin over several years—I also had the great pleasure of getting to know Ted personally. I’ve sometimes told those students who complained that Ted’s case studies are ‘dry’ that their problem is that they can’t hear Ted’s voice narrating the texts. The man is truly funny! To say his wit is dry is like saying the Sahara is hot: he is a master of the straight-faced quip, and I’ve been at talks Ted’s given where I embarrassed myself by laughing out loud while the rest of the audience stayed respectfully silent. It is often only that little gleam in his eye when he delivers a little aside or makes a seemingly innocent comment that gives him away—I’ve learned to look for that in conversations with Ted to make sure I’m not missing another gem.

Because I want to close this little essay with something more personal, I’d like to mention something else I’ve had the pleasure of sharing with Ted: a bicycle! Bikes are a very popular form of transportation in Berlin, and short-term visitors usually scramble to find a decent used one on arrival and then pass it on to someone else at departure. I was living there for an extended period, and Ted is an avid and fearless biker (if you know about those famous Berlin cobblestone bike paths). Ted was departing and I wanted a second bike to lend to friends who would be visiting, so I offered to hang on to Ted’s bike until his next visit. I had great fun telling visiting colleagues that they were going to be riding “Ted Porter’s bike,” the seat of which inevitably had to be significantly lowered for their use. A sign of Ted’s devotion to that mode of transit came one spring when Ted was in town for just a couple of days. He asked me to bring the bike to his hotel in the center of Berlin, and when I arrived, he was dressed for a ride. After we chatted for a bit, he hopped on for a nice little jaunt out to the Grunewald—a lovely forest west of Berlin “only” about a 15-20 km ride one way.

I admit that I’m not half the historian that Ted is, nor am I half the biker. But I’ll settle for that.

University of Illinois, Urbana-Champaign


When, in 1983, I started my PhD study of ‘the history of statistics in The Netherlands in the nineteenth century’, Henk Bos, one of my PhD supervisors, brought me into contact with Lorraine Daston. She was working in the history and philosophy of probability and statistics and belonged to a research group in Bielefeld on ‘The Probabilistic Revolution.’ Raine came to The Netherlands and invited me to come to Bielefeld as a guest for a few days. This was an invitation I eagerly accepted.

In Bielefeld I had the opportunity to participate in one of the weekly meetings. I remember that Raine took me to a classroom in which several scholars were already present and chatting. When the discussion between the scholars started, I was greatly impressed by their erudition. I realized that I had a great deal to learn and that this meeting was an excellent start. But I was most impressed by a certain male voice. I don’t remember what the man owning that voice was arguing. I do remember that he good-naturedly and without hesitation took the floor and made his point. What impressed me most was the tone with which he argued. The speaker had a remarkably low voice. Smooth and velvety were characterizations that came to mind. The voice turned out to be that of Ted Porter.

This is my first memory of Ted. I don’t know if I already knew him then as a scholar, but I soon read his thesis ‘The calculus of liberalism.’ The interplay of calculation and quantification on the one hand and liberal politics on the other was very recognizable to me. Dutch developments showed the same thing.

I don’t know if it was then or on another occasion that I had an exchange of ideas with Ted. We undoubtedly discussed statistics and quantification. But at some moment we changed subjects and talked about a topic that over the years also turned out to be a common interest: tour bicycling. I think that I did then not impress him with my scholarship in the history of statistics and quantification, but fortunately I managed to impress him with my ‘scholarship’ in traveling on ‘two wheels.’ I told him that I had spent my honeymoon on a bicycle, riding along the American west coast from northern Oregon to Santa Barbara in California. For many years my partner and I spent our holidays on two wheels; we made several tours not only through different regions in Europe, but also through the US and Canada. Ted liked to hear about these adventures. It was clear that a second link between Ted and me had been born.

Our common interest in the history of statistics and quantification also bore fruit. In the period when Ted was a guest professor in Utrecht, we had the opportunity to discuss a project on Dutch statistics that I was doing together with Paul Klep, an economic historian. I remember that, when Ted’s Trust in Numbers had just appeared and was very successful, we discussed the importance of book titles. In 2002 and 2008 two edited publications on the Dutch Statistical Mind appeared, the first on the period 1750-1850 and the second one, in two volumes, on the period 1850-1940. The editors chose the title carefully. Ted demonstrated his commitment to the enterprise by giving and writing a comment at the presentation of the first publication in 2002 and writing an essay review of the second in 2008.

It was clear from his first comments that he not only understood the somewhat peculiar phenomenon of statistics in The Netherlands in the period 1750 to 1850, but that he also placed it in the context of developments in other nations at the time. As a result of the strong roots of Dutch statistics in the German tradition of Statistik, originating in Göttingen, it started as a mostly qualitative science. Ted argued that the similarity was probably not only caused by the cultural overlap and close proximity of Germany and The Netherlands, but also by the fact that both countries were decentralized nations. After all, quantification and centralization have a reciprocal relationship. As a result it was rather different in nature than the beginning of statistics in France and England. The Netherlands needed the French occupation (1795-1813) to become a centralized country. During the occupation, statistics and quantification became stronger, but it would take a large part of the nineteenth century before everyone thought of statistics as numbers, let alone that it was identified with probabilities. Ted also took this to heart in his essay review of the second (double) volume. Although The Netherlands had become centralized, for a long time classical liberals managed to prevent statistics from becoming a systematic element in the government administration. But in the end it could not be avoided. In 1890 the social-anarchist F.J. Domela Nieuwenhuis clearly stated this inevitability in the Dutch Parliament: “What use is it in the long run to try to resist something that must ultimately happen, if the only question is whether it will happen a year sooner or a year later? It will happen; and nobody, not even the minister, can change that.” In addition, Ted recognized that volumes on statistics in one country have the possibility “to pay attention to governments and bureaucracies, emphasizing social history (even of science) over intellectual and philosophical themes.” They can demonstrate “the interactions between statistical knowledge, including the agencies that produce it, and the many functions of state.”

I met Ted on several occasions: at the conferences of the American History of Science Society, and at meetings dedicated to special themes like quantification or heredity, amongst others at the Max Planck Institute in Berlin. But thanks to his regular visits to The Netherlands, we had the opportunity to make lovely bicycle tours through the Dutch countryside, often through the polders and on the dikes that surround them. And we could together enjoy breaks on the terraces of small restaurants with nice views over the flat green land full of grazing black-and-white cows.

Thanks Ted for all the enjoyable moments I had with you!


Theodore M. Porter, Comment on The Statistical Mind in a Pre-Statistical Era: The Netherlands 1750-1850, edited by Paul M.M. Klep and Ida H. Stamhuis, delivered at the Free University Amsterdam on September 4, 2002. Centaurus 46 (2004) 318-322.

Theodore M. Porter, Essay Review: Quantitative Technologies, Administrative Practices, and Statistical Minds. Studium, 2 (2009), pp. 211–213. DOI: http://doi.org/10.18352/studium.1484

Vrije Universiteit Amsterdam


In the Fall of 1979 I began a correspondence with Ted Porter that has lasted 44 years. I had just moved to the University of Chicago from the University of Wisconsin, where I had taught statistics for 12 years, and a letter from Ted was forwarded to me in October. In addition to adapting to my new location I was starting a demanding term as a major statistics journal editor, but I immediately recognized a kindred spirit and set everything else aside to reply.

Despite the difference in our ages, there was a sense in which we were in exactly the same cohort. Ted was then a graduate student at Princeton, and two of our mutual friends had advised him to write to me as he was beginning to plan his dissertation, a work that would become his first book. I was a neophyte historian who had been recently tenured for purely technical work in mathematical statistics, and I had exploited this new sense of security by developing an interest (and a couple of articles) in the history of statistics, an interest that would lead to my first book. Ted asked for comments and suggestions after describing his plan to work on the history of statistics. He was well on his way, and I had little to add beside some references and encouragement. While we both were working on the history of statistics, there was little overlap; our interests were complementary, not competitive. Ironically, both first books appeared at the same time in late summer 1986.

Over the first few years of our correspondence, we exchanged letters, references, articles, and drafts of chapters, to what I believe was mutual benefit (at least I know I benefitted). We met in person in the September of 1982 at the ZiF (Zentrum für Interdisziplinäre Forschung) at the University of Bielefeld in Germany. Lorenz Krüger, with Ian Hacking, and Nancy Cartwright and a set of German scholars, had arranged a year-long project at ZiF on the history of statistics, and I had agreed to participate. In the summer of 1982 Ted wrote to me, “I am looking forward to meeting you in Bielefeld in a month or so. As I may not yet have informed you, I received a last-minute invitation to join the research group, which, happily, I was able to accept. I will be there for the entire year. As I recollect, you should be around during the winter.” What Ted did not then know is that I recently had backed out of my commitment due to my wife’s pregnancy with our fourth child, although I did attend the opening session in September 1982. It is possible that my retreat from the group had opened the way for Ted’s invitation; if so, I regard that as an important contribution to the history of science.

When our books appeared in the summer of 1986, we waited to learn how they were received, just as all new parents do. A major surprise came with the October 5, 1986, arrival of the Sunday New York Times, where our books were jointly reviewed in the Book Review section by the mathematician Morris Kline, in glowing terms ("An outstanding feature of Mr. Porter’s book is its depiction of the interrelationships between statistics and certain intellectual and social movements. ... Mr. Porter’s book is unfailingly interesting."). In that era the Times occupied a rarefied level as a platform for reviews, a position it has since ceded to the New York Review of Books and the Times Literary Supplement, among other outlets. I suspect we each may have had a slight thought of “why is the reviewer spending so much time on the other book?", but if so, that thought has long since vanished, overwhelmed by our pride of association. Those were the best of Times.

After the 1980s the correspondence slowed, until the time he got fully engaged with his biography of Karl Pearson (2004). I suspect most readers of that book do not fully appreciate the difficulties he faced and what a success he achieved despite them. First, there was Pearson’s huge published output and the immense archive of his correspondence. Pearson founded at least two journals and a half dozen series of studies, and he wrote or co-authored much of the content of all of these. A printed volume of his bibliography runs to 119 pages; the printed list of his archive is 164 pages long. And second, there was at the center of this, one of the most difficult personalities of the time, Pearson himself. When I first researched Pearson in the early 1980s I was blocked from the archive because Pearson’s son Egon had promised exclusive access to a young scholar, Bernard Norton, who was to write the definitive biography. But the more Norton got to know Pearson, the more he despised him, and he ended up abandoning the project. Ted’s success in giving a rounded and true picture of the man was a major achievement. I corresponded with Ted on some of the technical details of the work, and I did not fully agree with all he said, but I certainly respected his choices and consider the book a major success.

Ted’s most recent book, Genetics in the Madhouse (2018), was another signal achievement. I summed up my view in a blurb on its cover: “Porter’s masterful book casts the fresh light of sanity over a previously uncharted sea of data on madness. He brings analytical order to an intriguingly chaotic subject, illuminating the challenges of ‘big data’ from a past era when the plasticity of categorization resulted in data being deduced from conclusions, a problem with uncanny similarities to those we face today."

In the forty-four years of my interactions with Ted I enjoyed even the arguments. Sometimes I was successful, sometimes not, but I always learned from them and always appreciated the strong and principled mind he brought to bear on what mattered to him, as well as his wonderful sense of humor. I look forward to continued engagement in his retirement. Meanwhile, he remains one of the very few historians in the group Laplace and Friends (Google ‘Laplace and Friends’).

University of Chicago

Jessica WangTRUST IN TED

I first met Ted over dinner in February 1996, when I was a nervous job candidate at UCLA. Happily, I somehow got the position, but I was not familiar with Ted’s writings when I arrived in Los Angeles the following December, and shyness combined with the vicissitudes of assistant professorhood meant that my connection with Ted and history of science at UCLA grew somewhat slowly. During these years, I struggled as well to gain analytical purchase on a hazily defined project on technocratic politics in the 1930s that eventually turned out to be about reform social science and New Deal political economy. The desire to wrestle with expertise, scientific authority, and their place in public policy led me to Trust in Numbers, which immediately made me an ardent fan of Ted’s work. In the meantime, I also came to recognize and value Ted’s innate decency and integrity, intellectual honesty, and the droll, quick-witted, and completely hilarious sense of humor just beneath his diffident exterior. Numbers may be of dubious trustworthiness, but Ted can be relied upon.

Among many other contributions, Trust in Numbers shows how demands for quantitative exactitude as a guide to policymaking erode expert authority. Prior scholarship on the objectivity question in the postwar social sciences had generally assumed that quantification and its associated scientism reflected a quest to bolster the epistemic authority of the social sciences. Trust in Numbers persuasively revealed a counterintuitive reality. In the U.S. context, for example, Ted showed how Congressional demands for supposedly hard numbers to justify policy choices actually undercut the discretionary authority of experts. The essence of expertise, Ted contended, rests not upon demonstrations of unequivocal access to truth, but on the ability of epistemic communities to command trust in and respect for judgments that cannot be boiled down to instrumental forms of reasoning and automatic processes of calculation. Authority resides in the discernment and discretionary reason of the expert, and not in self-evident realities unveiled by rigorous and purely impersonal scientific methods. As much as it might portray itself otherwise, scientific knowledge cannot escape the application of critical judgment, and politics in search of self-governance cannot evade the need for social trust as a means of generating credibility, mutuality, and consensus.

These insights proved crucial in my own efforts to grapple with social scientific knowledge and the expansion of administrative power under the New Deal, and they later also shaped my understanding of medical authority in mid-nineteenth century America. To give a New Deal example, when the lawyers in charge of the newly created Securities and Exchange Commission fought in the 1930s for the administrative authority to develop and implement regulatory measures without constant and explicit authorization from Congress for each and every regulatory act, they did so on the grounds of expert judgment and administrative discretion as necessary foundations of governance in a modern, industrial age. Their arguments, which grew out of the pragmatist commitments of sociological jurisprudence and legal realism, created a policy apparatus that melded administrative flexibility, social scientific inquiry, and rule-making authority by experts under broad Congressional mandates. Amid the market failures that helped to produce the Great Depression, the SEC’s crackerjack legal and political minds made a powerful case for administrative authority as the only realistic means for addressing before the fact the irrational exuberance of irresponsible investment and financial skullduggery that would always outrun the pace of Congressional attention.

Trust in Numbers is just part of a larger body of work in which Ted has engaged productively and provocatively with scientists’ public personae and the nature of science as a form of public reason. His 2007 Distinguished Lecture at the History of Science Society, ‘How Science Became Technical,’ explored how scientists in the mid-twentieth century came to identify themselves with technical mastery and its instrumentalities rather than the progressive aspirations of enlightened public culture. In a nuclear age in which the Manhattan Project generation struggled over its relationship to political power and whether or not scientists had more to offer public life than the creation of ever more destructive technologies in service of the state, the narrowed vision of public possibility threatened serious consequences. At the same time, as Ted cautioned, the many wrong-headed and abhorrent aspirations of scientific thought, such as the ‘now almost unthinkable’ ideas of Karl Pearson, the subject of Ted’s 2004 biography, should give anyone second thoughts about scientific pretensions towards social uplift.

Ted extended this analysis with his idea of ‘thin description,’ which he presented in the HSS address and later elaborated upon in a 2012 essay that examined how technical reason tended towards a preference for surface explanation over unwieldy depth. Thin description, Ted suggested, helped to make scientific knowledge portable, by liberating it from locality, and also rendering knowledge more usable in public settings. I became much exercised by this notion, which I once ran with in a commentary at the HSS. There I riffed on the cold war American state and its immunity to social knowledge, in the sense of being highly resistant to seeing the complex realities of diverse parts of the world, and instead privileging modernization theory and other expert-generated thin descriptions as means of making sense of conditions in distant places. When my eye landed upon Ted in the audience, however, I suddenly realized a potentially fatal flaw in my argument—namely that it, too, relied upon thin description!

Ted’s ever-fertile historical imagination has since turned towards ‘funny numbers,’ numbers that are both suspicious in their provenance as well as darkly humorous. His devotees, myself included, eagerly await his future commentaries on this phenomenon. Indeed, it is impossible to contemplate this project as a worthwhile scholarly endeavor without Ted’s voice and inimitable sense of humor. Here I am deeply fortunate not to be simply an academic fangirl from afar, but to count Ted as a beloved friend whose ideas have always entertained and challenged, and whose observant wit and presence always create laughter.

Many of these happily comic moments are of the ‘you had to be there’ variety, but the following one merits a historical record. More than twenty years ago, Ted gave a keynote address at a workshop in Madison, Wisconsin, and afterwards, several of us relaxed for conversation at a nearby bar. When our drinks arrived, it turned out, much to our astonished bemusement, that a complete stranger had paid for Ted’s. What was it that accounted for this unanticipated act? Ted’s air of buoyant jocularity? His ageless boyish charm? The booming bass voice heard from across the room? Some other, indefinable je ne sais quoi? To this day, I have no idea of the explanation. Numbers are not the only thing that are funny.

University of British Columbia


The longer I share dinners and discussions with Ted Porter the more it feels as though our lives have been on parallel tracks from the beginning, that something like destiny has ruled the continuing inspiration that I have so long found in his work and his friendship. Well before I met him our lives seem to have been on parallel tracks (though his was newer and shinier). We grew up within fifty miles of one another in rural areas of Puget Sound in the state of Washington. Don’t think Seattle, think little towns like Chimacum and Gig Harbor, where working families also kept cows and chickens. Think too of a shared and mythologized Norwegian heritage, featuring hard work and self-discipline along with that devotion to hiking and biking through mountains and forests that many of Ted’s friends will recognize. Surely something of his famously dry wit derives in part from this upbringing, as in a line he liked to deliver with his characteristic twinkle, ‘have you heard about the Norwegian man who loved his wife so much he almost told her?’

Our more formal shared heritage, but still without knowing each other, began at Princeton University, where we both did PhDs in the history of science with Thomas Kuhn and Charles Gillispie. With such strong mentoring in the history of ideas it may seem surprising that Ted and I would both turn to a more socially and culturally informed history of science. But the social turn was well under way and people like the great cultural historian Carl Schorske were also there with alternative ideas. Within this stimulating environment, Ted developed the wholly original dissertation that brought him to the Bielefeld year on the Probabilistic Revolution, where The Rise of Statistical Thinking matured and where a friendship began that has only deepened with the years.

Historians of mathematics at the time typically looked for the origins of mathematical ideas in mathematics itself. Ted did something very different. He showed in expansive detail that the ‘thinking’ of statistical thinking in the nineteenth century had much less to do with mathematics than with social and cultural thought carried by analogy into new areas. James Clerk Maxwell, for example, initially developed his gas theory by analogy with Adolphe Quetelet’s use of the error law for social statistics. That perspective on origins became crucial to my own pursuit during our Bielefeld year of the cultural origins of the concept of ‘statistical causality,’ which emerged in German psychology and history well before it became the key idea of quantum mechanics.

Having already established his reputation at Bielefeld for rigor, creativity, and humor, Ted soon went on to a regular faculty position at the University of Virginia. We might have lost close contact at that point but fate seemingly intervened to bring him to me at UCLA in 1991. It was fickle fate as I was just leaving for Princeton, but we connected nonetheless.

At that point Ted was already well into his next big book, Trust in Numbers, with its counterintuitive but seminal thesis that bureaucracies rely on non-subjective numbers for their claims to authority when they are professionally weak rather than when they are strong. And now once again our pursuits intersected. He agreed to contribute one of his thought-provoking insights associated with Trust in Numbers to my workshop volume on The Values of Precision. His ‘Precision and Trust: Early Victorian Insurance and the Politics of Calculation,’ argued that ‘There is a politics of precision. . . . Precision in science, too, must be understood as a form of knowledge sanctioned by a community . . . .’ And it is the community sanction that allows the numbers to travel like objects.

Ted’s presence at UCLA and our shared interests and values helped to call me back to UCLA to occupy the office next to his. He was then working on Karl Pearson, the Scientific Life in a Statistical Age. Listening to him talk about his findings in the huge Pearson archive taught me something about his methods that I should have recognized earlier. I had spent many long hours in archives but almost always in pursuit of material that would help me validate and expand a narrative perspective that I brought with me. With Ted instead the archive itself took priority. His task was to animate it, and with that Pearson’s life in a statistical age emerged with fresh authenticity. As Ian Hacking expressed it already for the dust jacket of Trust in Numbers, it was “written with the precision of an historian skilled at bringing to life the dustiest of bureaucratic archives.”

This theme for the dustiest of archives finds for me its most brilliantly consequential expression in Genetics in the Madhouse. The dense tables constructed by asylum directors to try to understand the relationship of mental illness to heredity may remind us of the “tabular statements” that Charles Dickens ridiculed in Hard Times. But Ted’s animation of these statistical tables grounded the big thesis of the book, that the history of genetics had its origins in the analysis of heredity in the nineteenth century asylums of Britain and Europe long before it centered on genes as the carriers of heredity. It is striking that historians of genetics, with few exceptions, have been slow to recognize this crucial historical process. It takes us back to The Rise of Statistical Thinking where Ted showed how statistics emerged from social and cultural concerns long before it became a set of mathematical techniques.

All of this exposure to Ted’s intellectual accomplishments might have been reward enough for a person in the office next door but far the most enjoyable times for me stemmed from the course we co-taught for many years with the pretentious title ‘History of Modern Thought.’ We lectured to self-selecting first-year students with an unusual capacity for digesting many pages per week of often difficult text (with regular complaints). Nothing surprised them (and me) more than Ted’s lecture on Jeremy Bentham’s utilitarianism. Well into Bentham’s theory of punishment, we found ourselves in Gilbert and Sullivan’s musical sendup of the British ruling class in The Mikado, for whom just punishment for trivial offenses meant beheading. And singing lines of the Mikado himself was our own Professor Ted Porter in his rich baritone:

My object all sublime
I shall achieve in time—
To let the punishment fit the crime—
The punishment fit the crime.

(With applause from 200 students and 1 professor who will never forget Bentham’s theory.)

University of California, Los Angeles


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