Not all censorship looks like deletion.
Sometimes it looks like silence—the quiet omission of inconvenient categories, awkward outcomes, or unapproved questions.
Nowhere is this more apparent than in modern health research, where one of the most fundamental variables—biological sex—is increasingly minimized, conflated with gender identity, or removed entirely from analysis.
It’s done, we’re told, in the name of inclusivity. But who benefits from a science that’s afraid to say “male” or “female”? And who loses when biological differences are blurred to the point of irrelevance?
This isn’t a culture war. This is data integrity.
When Sex Stops Being a Variable
For decades, women were excluded from clinical trials under the assumption that male bodies were the “default.” The result? Entire generations of medications, dosages, and diagnostics were developed without understanding how they affected women.
That oversight wasn’t just negligent. It was deadly.
Today, we risk repeating the mistake—this time under a different banner. In an effort to appear inclusive, some health research now avoids disaggregating data by sex at all. Others substitute “gender” in place of biological reality, muddying the waters between identity and physiology.
You can’t treat what you refuse to measure. And you can’t measure what you’ve erased.
The Olivia Dobbs Case
A recent example comes from Olivia Dobbs, a neuroscience PhD candidate whose Medium article, “When Science Is Censored,” detailed her experience of institutional discomfort when she argued that sex is a necessary variable in research.
She was accused of being transphobic. Her work was questioned. But her central argument—that sex-based biology affects health outcomes—was never truly refuted. It was reframed.
Sound familiar?
Reframing as Scientific Control
As we explored in our previous article on reframing vs. fact-checking, this technique isn’t about disproving a claim. It’s about repackaging it to make it easier to dismiss.
Rather than engage with the question, the strategy is to:
- Shift the focus to intent or identity
- Politicize the premise
- Cast doubt through association, not evidence
And suddenly, a call for better data becomes a cultural offense.
Why It Matters
Biological sex matters in:
- Drug metabolism
- Heart disease symptoms
- Pain thresholds
- Immune response
- Vaccine effects
- Hormonal changes
Failing to separate male and female data in these contexts isn’t inclusion. It’s distortion.
If science doesn’t reflect biological realities, then who’s it serving? If acknowledging sex differences is seen as exclusionary, then what happens to women whose health outcomes already lag behind?
From Missing Data to Missed Diagnoses
Omitting sex-based distinctions isn’t just a design flaw. It’s a pipeline of misinformation. When sex-specific variables are missing at the research level, they stay missing at the clinical level. Diagnoses are missed. Symptoms are misread. Treatments fail.
We know this. We’ve seen it before.
So why are we doing it again?
It’s Not Anti-Inclusion to Ask Better Questions
Let’s be clear: calling for rigorous, sex-specific research is not a denial of gender identity. It’s a demand for scientific accuracy.
People can identify however they wish. But biology doesn’t disappear because it’s uncomfortable. A uterus doesn’t metabolize medication like a prostate. Pretending otherwise is not progress. It’s posturing.
In science, the goal isn’t to be politically correct. It’s to be correct.
So What Now?
Ask what categories are missing. Look for what was measured—and what wasn’t. Question whether the findings reflect reality, or a version of it that avoids controversy.
Because when research starts editing itself before the evidence is even in, what we get isn’t science.
It’s storytelling.
Further Reading: When Inclusion Becomes Omission
If you’re questioning how science defines its categories—and what happens when those categories are erased—you’re not alone. These books and articles offer deeper insight into the consequences of removing sex and gender as meaningful variables in health research.
Books
The following books are linked to Amazon.com for your convenience. If you decide to purchase through these links, we may earn a small commission — at no extra cost to you.
Invisible Women: Data Bias in a World Designed for Men [My Review]
By Caroline Criado Perez
A compelling, data-rich exploration of how women have been systematically left out of data collection across industries—including medicine—with real-world consequences.
Sex Matters: How Male-Centric Medicine Endangers Women’s Health and What We Can Do About It [amazon.com]
By Alyson J. McGregor, MD
A physician’s firsthand account of how neglecting sex differences in medicine leads to misdiagnoses, improper treatment, and poorer outcomes for women.
The End of Gender: Debunking the Myths about Sex and Identity in Our Society [amazon.com]
By Debra Soh
A controversial but deeply researched argument on the importance of biological sex in science, society, and mental health.
Articles & Reports
When Science Is Censored – medium.com
Olivia Dobbs
A neuroscientist’s reflection on how advocating for sex-based research integrity was reframed as exclusionary.
Inclusion Policies and Sex/Gender Research – NIH
The U.S. National Institutes of Health’s official stance on why sex and gender should not be ignored in health science.
Sex, gender, and medical data: a way forward – The BMJ
A thoughtful critique from British Medical Journal contributors on why conflating sex and gender undermines data accuracy.
Truth-seeking means asking better questions—even when it challenges comfort or convention. Keep digging. Keep reading. Keep thinking.
This article is part of our “Automated Authority” series, examining how science, technology, and institutional culture shape public understanding. Explore other articles in the automated authority series.
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