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Abstract
Amidst proliferating threats to trans rights, transgender activists are using data and data activism to advocate for and to protect trans communities. This transgender-led study asks “How do trans activists use data in their activism?” We interviewed 16 activists engaged in trans community care: from community healthcare to media production to policy making, our participants are making and using data about trans people to serve and support trans communities. Our findings reveal that participants use tactical approaches to data and data science that were consistent with existing data activist literature and contemporary approaches to data refusal. However, what emerged were more than sets of tactics — our participants described ways of knowing with and about data that are grounded in their experiences of (racialized, disabled, aging, queer) transness. Taken together, we consider these ways of knowing to be a trans data epistemology. 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.
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A new academic paper argues that data should serve activism over truth.
By: Colin Wright
Published: Nov 3, 2025
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 authors say they interviewed a handful of “trans activists” who use “data and data activism to advocate for and to protect trans communities.” But what they call “data activism” however, bears no resemblance to objective research. They define it as a “spectrum of behaviors that use systemic information to enact political change and care for communities.” One end of the “spectrum,” they explain, “resists the datification of their existences.” The other “leverages data to promote ‘alternative narratives of the social reality, questioning the truthfulness of other representations, denouncing injustice and advocating for change.’”
This is insidious precisely because they understand the power of the word data. Data suggests precision, objectivity, and real-world measurement. When used honestly, data derived from real-world measurements is one of the most reliable tools humans have for finding truth. But the authors use data not to understand reality, but to manipulate how people see reality. They’re turning the public’s trust in data into a political weapon to advance activist goals. This represents an assault on the scientific method itself, and it erodes public trust in the very institutions built to safeguard truth.
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.
From that premise they outline the “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
Data makes us visible to institutions.
Each of these pillars represents a step away from the scientific method and toward blatant research misconduct.
The first pillar—“categories are provisional and productive”—rejects the idea that categories can or should reflect reality at all. “It is by now a truism that categories are political,” they write. Trans activists, we are told, “shape, remold, and add categories to create future trans worlds.” One participant even boasts about inventing new labels so that “we have language for things that we want there to be in the world even when those things have not yet materialized.” In other words, they’re using language to conjure new realities. A legitimate academic would call this data fabrication.
The second pillar—“data can be a tool for community care”—goes further. The authors describe the demand for empirical evidence “a perversion of knowledge” that furthers what they call “the datafication of injustice.” According to them, requiring proof before acting against an alleged harm creates “a freeze state, unable to be broken until a complete data-based picture emerges.” One participant complains, “The frustrating part about the need for data is that we have to use it as proof because no one believes trans people without it.” The authors call this “testimonial injustice.” But skepticism isn’t oppression. Rather, it’s foundational to science. As physicist Richard Feynman said, “The first principle is that you must not fool yourself—and you are the easiest person to fool.” The whole point of skepticism and demanding evidence is to prevent self-deception.
Yet the authors view disbelief itself as a form of harm. They write approvingly about using data rhetorically rather than empirically to produce the appearance of evidence in service of pre-decided conclusions. “Our participants reflected an understanding of data as rhetoric,” the authors write. But if data is simply a rhetorical device, then accuracy becomes optional.
That brings us to their third and most alarming pillar: “community well-being is more important than ‘accurate’ data.”
Here they reject objectivity altogether. “Actionable and useful data for community care,” they write, [is] the utmost priority over true, accurate, or verifiable data.” This is an open admission that truth is seen as secondary to furthering activist goals. They praise what they call “community-first caretaking,” where “lowering barriers to care” is “more important than making sure that everything is ‘true.’” They even celebrate organizations that issue medical authorization letters in “three days, no barriers”—a practice that would be considered medical fraud in any healthcare system not captured by ideology.
The principle that “community well-being is more important than ‘accurate’ data” is indistinguishable from the claim that lying is acceptable when the truth is politically inconvenient.
But truth and well-being can’t be separated. You can’t claim to care about people while discarding the very information needed to protect them. That’s especially true in medicine, where accuracy is necessary to reduce harm and save lives. “Gender-affirming” procedures that sterilize children and remove their healthy body parts would never have been allowed if data accuracy was held in high regard. Detransitioners now living with permanent medical harm are living proof of what happens when “rhetorically useful” data is prioritized over accurate data. Their suffering is the human cost of “data activism.”
The fourth pillar—“data makes us visible to institutions”—continues the theme of placing politics over truth. Here, data is no longer a measurement of reality but a lobbying tool. One participant brags about reframing “gender-affirming care” as “preventative care” by claiming that it “significantly decreases suicide attempts.” That claim is false, but the authors repeat it uncritically as an example of what they call “reframing work.” Perhaps repeating this false claim isn’t accidental and is simply an act of “data activism” itself. This might explain why gender activists routinely dismiss or bury data on detransitioners, push debunked studies, and treat any challenge to their narrative as bigotry.
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.
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Basically, "lying becomes truth when it comes from us."
This is academic gibberish intended to gaslight society into blind, unquestioning faith when it comes to "trans" claims.
This absolutely gives the game away that everything "trans" is false and unscientific. If "trans" asssertions were actually true, they wouldn't need to wholesale invent an epistemology to justify it and try to fool everyone. They could just present the data and the evidence and it would be indisputable.
When people cite the "experts" who claim that regret and detransition are "less than 1%," these are the "experts" they're citing.
