One of the recurrent themes on this site—and in the new anthology The War on Science, including the paper byLuana and Maroja and me—is the erosion of scientific standards by ideology. Now a new paper in the peer-reviewed journal Big Data & Society (first title below), analyzed by Colin Wright on his website (second title), shows more than anything the explicit antiscientific aims of some ideologues. And those aims include clear guidance to prioritize ideology and politics over truth. Nowhere else have i seen this aim stated more blatantly.
In this case, the ideology promoted to distort or efface truth is “trans data epistomology”: a way to deal with data on trans issues. (As you know, empirical data, because they sometimes counteract accepted trans ideologies, have been controversial, leading to withholding of data that has real effects on human beings.)
I hasten to add that the distortion of data and prioritizing of politics over truth can be and has been applied to any group that does “science” with a political agenda—not just minority groups but entire organizations like scientific journals, medical schools, and professional organizations. I emphasize this because trans matters are the hottest of political hot potatoes, but what this paper exemplifies is not at all unique to trans issues, and calling it out is not “transphobic”. In this time of extreme political division, science has become a tool not for finding truth, but for advancing your cause, no matter what the cause may be. Damn the truth, and full steam ahead.
The authors of this paper (again, it’s peer-reviewed) conducted 13 interviews of activists involved in “trans community care” and, from the 16 people involved in these interviews, the authors derived four pillars of what they call “trans data epistemology”, which turns out to involve, as Colin notes, ways you can use data to advance your cause.
Click the title below to read the paper:
Here’s part of the abstract; I’ve bolded the four pillars, but pay attention to the third one: “community well-being is more important than ‘accurate’ data”. The last one, “data makes us visible to institutions,” apparently means “reframing your data in a way that serves your needs.”
Drawing on literature from trans theory, data activism, critical data studies, philosophy, and critical social theory we offer a narrative of trans people as creators of knowledge, data-based and otherwise, undergirded by four pillars of a trans data epistemology: categories are provisional and productive, data can be a tool of community care, community well-being is more important than “accurate” data, and data makes us visible to institutions.
This is from the paper’s section on “pillar 3”: prioritizing ideology over truth:
Community well-being is more important than “accurate” data
Trans communities are experiencing an emergency. Well, it was already an emergency, but this is an epidemic. This is a crisis. This is, stop what you’re doing. We have to help now, today. And sometimes these pieces of data really can be a very strong call to action. (George)In this pillar, we examine how participants prioritized actionable data for the trans community. Our participants reflected an understanding of data as rhetoric, as merely “one mode of conveying information” (Haarman, 2021: 35), not the only mode. When data is simply one of many ways of conveying information, it does not need to be viewed as the canonical source of truth. Our participants repeatedly emphasized that actionable and useful data for community care was the utmost priority over true, accurate, or verifiable data. We do not mean to undermine the meticulous data work of our participants but to emphasize the desired outcome of community well-being of their data work. This aspect of trans data epistemology is consonant with the idea that data is for community care.
This is an academic way of saying that there are other ways of knowing besides the data itself, and data doesn’t have to be the “canonical source of truth.” In fact, when the data conflict with “community care,” you give priority to the latter. For things like “affirmative care” in gender medicine, this has obvious implications. One example is the withholding of data that counteract accepted ideology, like recent data showing that untreated gender dysphoria does not increase the suicide rate, or that affirmative care does not bolster mental health.
I’ll leave you to read the paper itself and Colin’s analysis below (I’ll quote him a bit), but want to add one part of the paper that’s becoming increasingly commonplace: “author positionality”—statements in which authors reveal aspects of their personal life, including their activities and ideologies. Here’s the positionality statement of the second author from the University of Washington (the first author works at MIT):
Amelia Lee Doğan: I came to this project after its development as a trans person interested in activism and data. My experience include working part-time for a university LGBTQ+ office for several years and researching other activists communities’ data and technical needs. I had no direct contact with any of the interview participants but their words and work truly made me cry at how other trans people are making this world a little better for us. Especially, as a trans young person of color, it was an honor to get to hear our elders talk about how they have fought and continue to fight and care for us.
Stevens’s statement is pretty much the same, except for the crying part. But is it any wonder that authors so deeply dedicated to a specific ideological aim are willing to allow distortion of data to achieve that aim?
On his site Reality’s Last Stand, Colin gives a succinct and, in my view, an accurate summary of the paper and its problems. Click below to read it:
I’ll give a few quotes, but if you like Colin’s analysis and work you should subscribe to his site.
Over the past few decades, universities have churned out a steady stream of papers so detached from reality that they often read like parodies. Many of them have been highlghted right here on Reality’s Last Stand: the infamous “feminist glaciology” paper that sought to “decolonize” ice; the surreal paper where two “hydrosexual” researchers married brine shrimp and made love to a lake; and the deeply disturbing pieces on “queering babies” and questioning childhood sexual innocence. Those were insane. Others—like those calling to “Indigenize” and “decolonize” medicine by rejecting the scientific method—are not just ridiculous, but genuinely dangerous.
Now, a new peer-reviewed article in Big Data & Society breaks new ground by openly arguing that lying with data is not only acceptable but morally required when it comes to transgender issues.
The paper, titled “Trans Data Epistemologies: Transgender Ways of Knowing with Data,” was written by Nikko Stevens, an assistant professor of statistical and data sciences at Smith College, and Amelia Lee Doğan, a PhD candidate at the University of Washington and research affiliate with MIT’s Data + Feminism Lab. What makes this paper truly remarkable is how the authors openly admit that “truth” in their work takes a back seat to politics. “Actionable and useful data for community care,” they write, is “the utmost priority over true, accurate, or verifiable data.”
They are so ideologically blinkered that they’re not even hiding the fact that they’re committing research misconduct. They’re openly celebrating it in a peer-reviewed journal. The very existence of “data activism” as an academic field shows just how thoroughly higher education has been captured by ideology.
. . .The paper presents this approach as a “trans data epistemology,” supposedly a new “way of knowing” based on “trans experiences.” The authors argue that “mainstream Western epistemology”—the normal way of doing science—has historically favored the perspectives of the dominant group—white, cisgender, heterosexual men.” Because there’s “no universal knowledge system,” they claim, “epistemologies based solely on the perspectives of one group are necessarily limited and incomplete.” Every group must therefore have its own truth, and the truth according to marginalized groups trumps all others.
In other words, they believe truth itself depends on identity. Instead of minimizing bias, as real scientists strive to do, these authors maximize it.
Colin goes through the four pillars of the new epistemology, which remind me of the indigenous “ways of knowing” capturing New Zealand. Colin views the new epistemology as “an assault on the scientific method itself, and it erodes public trust in the very institutions built to safeguard truth.” Note that this assault comes from the left flank of politics.
There’s a lot more, but I’ll just give Colin’s conclusion and, below that, one of my favorite quotes about science.
Colin:
Underlying all of this is the belief that scientific standards are oppressive. The authors proudly conclude that their “trans data epistemology stands apart from hegemonic values about data, in which data is a mimetic representation of reality [and] a way to discern truths about the world through big data insights.” The idea that “represent[ing] reality” with data is “hegemonic” is absurd.
It’s hard to overstate how blatantly this paper rejects the basic principles that make science possible. Principles that have slowly evolved over centuries to reduce bias and uncover truth. That this paper survived the gauntlet of peer-review at Big Data & Society—supposedly a top journal in the field by impact—shows just how far the academic world has fallen.
And Richard Feynman, on the Challenger disaster:
For a successful technology, reality must take precedence over public relations, for nature cannot be fooled.
The only silver lining to this dreadful paper is that hardly anybody will read it, as it’s buried in a rather obscure journal. On the other hand, people need to know stuff like this so they can see how real, objective science is going down the drain, washed away by the shower of ideology. And “regular” people are starting to realize this because some ideological nonsense, like the view that there is a spectrum of biological sex in humans, has made it into the public ear.
Shame on this journal, and shame on the peer reviews who denigrate truth in favor of politics.
All I have to add are a couple quotes/expressions :
“The first principle is you must not fool yourself – and you are the easiest person to fool.”
Richard Feynman
1974 Caltech commencement address
(Details upon request 😁)
Nullius in Verba
-Latin motto of The Royal Society ca. 1660
One translation : “Take nobody’s word for it”
…. and a bonus, salient saying I found recently :
Tradition is not the worship of ashes, but the preservation of fire
… and of course, it is possible to INVERT or SUBVERT each and every one of those! In which case, PCC(E)’s selected Feynman quote comes in handy :
“… Nature cannot be fooled.”
QED
These quotes go well with:
irrationalism, i.e., disbelief in objective fact, arises almost always from the desire to assert something for which there is no evidence, or to deny something for which there is very good evidence. But the belief in objective fact always persists as regards particular practical questions, such as investments or engaging servants. And if fact can be made the test of the truth of our beliefs anywhere, it should be the test everywhere, leading to agnosticism wherever it cannot be applied. (11-12) (34-35)
Bertrand Russell: Can man be rational? in: The will to doubt. New York, 1958, 9-16 (also in: Sceptical essays. Routledge, 2004 [1928], 32-39)
One must have the nerve to assert that, while people are entitled to their illusions, they are not entitled to a limitless enjoyment of them and they are not entitled to impose them upon others.
Christopher Hitchens, Letters to a Young Contrarian (Basic Books, 2001), ch.12 (p.82)
Alice laughed: “There’s no use trying,” she said; “one can’t believe impossible things.” “I daresay you haven’t had much practice,” said the Queen. “When I was younger, I always did it for half an hour a day. Why, sometimes I’ve believed as many as six impossible things before breakfast.
Lewis Carroll: Through the Looking-Glass and what Alice found there. 1871 (Ch.5 Wool and Water, p.62 of Folio edition)
It does not make any difference how smart you are, who made the guess, or what his name is – if it disagrees with experiment it is wrong. That is all there is to it.
-Richard P. Feynman
The Character of Physical Law (1965)
Chapter 7, “Seeking New Laws”, p.150 (Modern Library edition, 1994)
Love those! Gonna write ’em down…
… I’m checking my notes, and my Feynman reference is nearly verbatim – wonder how that happened! 😁
Feynman’s principle – “The first thing is not to fool yourself…”
Modern academic’s principle – “The first thing is to fool anyone you can to advance your cause”
With a coda: fooling yourself first makes you more convincing when you then try to fool others.
Yes, and that’s part of the neo-Marxian ideology. “Science” is just one of the hegemonic devices that is used to oppress the oppressed. The authors’ attitudes are not just tactical falsehoods; they are strategic. I once again recommend James Lindsay’s “No, the Woke Won’t Debate You. Here’s Why.” It is a, relatively, short exposition of the mindset.
Of course it’s oppressive, even exterminatory, of anti-empirical nonsense.
It’s epistemic violence.
I kid you not.
Jerry seems right about this being an esoteric journal, although this wacko article seems “out there” even for this journal. But sadly, the journal universe is as bad as the www (to use an archaic expression) for silos that pander to every taste. So rather than remaining hidden, this article will be found and disseminated in journals and on sites that specialize in such flaky stuff as long as it promotes the right ideology and fits the perverse view of “research” it represents.
My colleagues on the other side of campus wonder why scientists and engineers roll their eyes at the idea of “qualitative methods.” This is why.
The plural of anecdote is not data.
Here’s my favorite relevant quote from Alan Sokal: ” The bottom line is this: It is never justified to distort the facts in the service of a social or political cause, no matter how just. If the cause is truly just, then it can be defended in full acceptance of the facts about the real world; if that cannot be done, then the cause is not just.”
Thanks for this — it lead me back to several good posts & articles (including WEIT May 26, 2024 & therein) worth reviewing or reading anew. I have enjoyed Sokal’s writing since the late -90’s when I read the Dawkins review in Nature and bought Sokal & Bricmont Fashionable Nonsense.
Sadly, “truly just” is not an empirical predicate.
The Noble Lie is alive and well.
Oh, it is alive and kicking:
Jackob L. Mackey: Virtuous lies. in: Lawrence M. Eppard, Jacob L. Mackey & Lee Jussim (eds.): The Poisoning of the American Mind. George Mason University Press, 2024, 196-204 [pages in ebook pdf: 204-212]
Mackey distinguishes between virtuous lies and noble lies (and luxury beliefs, a term coined by the psychologist Rob Henderson):
[210] Some Consequences of Virtuous Lies
the promise of virtuous lies is a false one
First, the internet has put any citizen with even a modicum of interest and a free Sunday afternoon in a position to adjudicate these claims for herself.
Second, the lies will alienate at least as many people as they inspire.
[When people figure out that they are being lied to] This will create, or is already creating, a division in which a side consisting of tribally committed virtuous liars faces off against a side consisting of people who resent being lied to. This division is and will be toxic to our politics and hence to our democracy
[211] The cost of the lie is paid as a psychological toll on all Americans but on Black Americans especially: the needless psychological suffering that results from hearing that you are being “hunted” by agents of the state in your own country
[211] The cost of the lie is paid as damage to our perceptions of Black and White race relations. Gallup has polled Americans on this almost every year since 2001.39 In 2001, 70% of Black Americans said race relations were good. In 2021, not even half as many, 33%, could make that affirmation. The drop-off began in earnest in 2013, right around when use of terms like “racism” began to rise spectacularly in the media40 41 and the newly formed Black Lives Matter began its messaging campaign.
The cost of the lie is not only ill-conceived campaigns to “defund” but also the destruction of trust between communities and police, especially Black communities, whose disproportionate victimization by criminals shows they need policing, good policing, the most. The cost of the lie is Black Americans’ sense of alienation within their own country. The cost of the lie is the creation of preconditions for destructive rioting the next time a cop is caught on camera killing a Black person, whether under legally justifiable circumstances or not.
There is a final cost to be reckoned with. Police killings do not ultimately constitute a distinctly “Black” issue, and a narrative that casts it as such has inherent limitations.
[212] The upshot is that virtuous lies, whether about the police or about any other matter of concern, will get us nowhere. Only if the media and knowledge-producing classes eschew such lies and hew closer to the truth can we hope to depolarize our discourse, restore faith in our information-generating institutions, and bring together a broad swath of the country in solidarity to confront the challenges that face all of us as citizens.
Judging from the excerpts you cite, it seems that the authors throw the word “data” about as if they understand what it means. They apparently do not. It would be interesting for someone to dig into what, exactly, “data” means in trans data epistemology.* My guess is that the term means nothing like what it means to a scientist. It appears to be as malleable as the postmodernist meaning of “truth.”
*I’m not suggesting that our host take on this task.
Some days I’m absolutely amazed we ever had an Enlightenment, an Industrial Revolution, and science of any kind.
This paper has made it a drinking day here in my office.
This is the type article my far right wing acquaintances will seize on to dismiss any and every article they don’t like (climate change, vaccines, etc.).
Why we continue to serve up “own goals” like this is beyond my comprehension.
They make arguments claiming any impartial integrity of science untenable as we publish this article bragging about bias.
Not gonna keep fighting the good fight only to get shot in the back.
Don’t piss down my back and tell me it’s raining.
Take your pick.
Exactly. We pay a very high price for abandoning rigour.
Vaccine skeptics and climate change deniers rush in.
“Trust science? They don’t even know what a woman is.”
Not a scientist, but I’ve always thought that peer-review scrutiny was pretty tough–that the reviewers had real expertise and could judge the accuracy of the articles they reviewed. What do we surmise happened in this case?
(1) Ideological capture of various journals, part of the “Long March through institutions”.
(2) A lot of slackness/corruption in the whole academic publishing business/racket.
“Every great cause begins as a movement, becomes a business, and eventually degenerates into a racket.” (Eric Hoffer, The Temper of Our Time)
(3) Similar slackness/corruption in the general academic business….
Different subject areas have different attitudes to refereeing and criteria for acceptance or rejection of papers:
1) Is it correct?
2) Is it a contribution to knowledge?
3) Does it agree with me?
You can probably make a guess as to which subject areas use which criteria.
I saw Colin post about this nonsense on X. Words fail me.
Earlier this year the UK government published an independent report it had commissioned from professor Alice Sullivan on the importance of data integrity around sex and gender: https://www.gov.uk/government/publications/independent-review-of-data-statistics-and-research-on-sex-and-gender
The sheer brazenness is almost impressive.
The Columbia University statistician Andrew Gelman is a prolific blogger who analyzes & criticizes research and methods (especially statistical methods in social sciences, but something for everyone). I keep the link to this old post about “zombie hypotheses” that can’t be killed by mere data.
https://statmodeling.stat.columbia.edu/2016/09/21/what-has-happened-down-here-is-the-winds-have-changed
Among the hundreds of comments on that post and the problem that it examines, this one by reader Plucky was prescient because it predicted exactly the kind of corruption that you highlighted here.
“The key problem…is this sentence: “Ultimately, Science is a community, and we are all in it together”…Science is not a community, it is a method…Obviously, Science is something practiced by people in collaboration, around which a community will naturally form, but the…fundamental problem with defining Science as “ultimately… a community” is that communities do not generally value the truth over their members’ well-being [and so they] need very strong commitments both individually and institutionally to avoid corruption.”
I note (with some horror) that Amelia Lee Doğan is described as “a PhD candidate”. At my university (and any reputable university) falsifying data this way would lead to “[failing] the degree in respect of which Research Misconduct is established”, not being allowed to “submit work for any research degree of the University”, and being expelled. Will her dissertation examiners be chosen to ensure they turn a blind eye to her misconduct?
For more, see: https://ameliadogan.github.io/ Ms.Dogan
specializes in “…how we can use data and build technology in more just and sustainable ways for and with marginalized communities”.
Thanks Jon. I see at her website that this paper got “an honourable mention” at the ‘Conference on Computer-Supported Cooperative Work & Social Computing’, where Amelia presented it. The conference abstract says she will discuss “resolving, researching, recording, and refusing and using data.”
Did she mean “reusing”; is this, therefore, the definition of ‘Freudian slip’?
This paper in Big Data and Society belongs aside another, similar sign of the times, entitled “Decolonize Scientific Institutions” at https://www.nature.com/articles/d41586-025-02516-8 . [Kent Osband comments on this paper in Heterodox Stem.]
The “decolonization” party line, and the four pillars of genderwang abuse of data, both reveal an embarrassing aspect of modern academic life: our contemporary wokeism makes the Lysenkoism in the galaxy far away in ~1950 look relatively scientific. Ye gods!
As our host (and Luana Maroja, in their outstanding chapter in “The War on Science”) points out, this sabotage of the scientific method itself is far more dangerous in the long run than the Trump admin’s temporary blockage of a limited number of research grants. Who could have imagined, when post-modernist affectations became evident in the groves of academe 40 years ago, that they would spread this far!