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Judge Christopher Cooper found that the Teen Pregnancy Prevention solicitations cited studies that either do not exist or do not say what HHS claimed, and he held the whole policy rather than asking for a corrected bibliography.
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Somebody opened the solicitation and looked the references up: a journal search, and five of the seven cited articles did not survive it [4]. Seventy-one percent of the cited support for a policy change was knocked out by the cheapest check available [11].
What Judge Cooper, who joined the federal bench in Washington in 2014 [10], did with that is the part worth copying into an operator's risk register. The remedy landed on the decision, not the bibliography: he folded the citation problem into a finding that the changes were likely arbitrary and capricious and that the government had not supplied sufficient evidence [2], and put the rewrite on hold while the case continues [1].
The assumption behind a model in the drafting path is that it produces a draft, a human reviews it, and the human catches the errors. In practice, reviewers read the prose, because the prose is where the argument lives, and skim the references, because a formatted citation looks like a claim somebody else already checked. Authors, volume, page range, a DOI shape. That formatting is what gets a reference waved through, and it is the part a language model produces most fluently.
Worth separating the thing being pitched from the thing being done. The pitch is drafting help. What a grant solicitation actually is, is an evidentiary record that outside parties act on and can litigate against. Note also that nobody has established which tool was used, or that one was; Cooper inferred it from the fingerprint, writing that the solicitations "(remarkably) reference public health studies that appear either not to exist or not to support the propositions for which they are cited," which he called "a hallmark of AI-generated citations" [3]. Techdirt, which is plainly hostile to the agency's leadership, lines this up with a report to Congress on the CDC's COVID vaccine recommendations that cited unpublished studies and studies whose own text asked not to be cited yet [8], and with the MAHA Report, where cited studies could not be found and the AI explanation was, in Techdirt's own words, wide speculation [9]. The lesson survives the uncertainty. An unverifiable reference is a defect whoever typed it.
A sorting rule you can run tomorrow. Axis one: does someone outside your organisation take an action based on this document. Axis two: could a stranger check every factual claim in it inside an hour. Documents high on both are where fabrication gets found by a party whose interests differ from yours, and where the remedy is withdrawal rather than correction. Grant solicitations qualify. So does a compliance filing, a security questionnaire, or any pricing claim with a footnote attached. In that quadrant, reference checking is a gate before publication rather than a step inside review, and the checker cannot be the author.
The tradeoff is that this is slow and will feel like theatre. Most of what you publish nobody audits, and you will spend minutes per reference proving something that was already true. The counterweight is the position HHS is now in, where the fix was no longer available at the level of a footnote because the arithmetic on the citations had already been written into an opinion [11].
Ranked by verification strength, evidence, and original report placement.
Cooper wrote that the grant solicitations "(remarkably) reference public health studies that appear either not to exist or not to support the propositions for which they are cited" and described this as "a hallmark of AI-generated citations."
U.S. District Judge Christopher Cooper granted a preliminary injunction putting a hold on HHS's changes to Teen Pregnancy Prevention Program grant solicitations while the lawsuit continues.
Cooper called the HHS changes "likely arbitrary and capricious" and said the government had failed to provide sufficient evidence for its policy.
According to Cooper, of seven cited articles, two appeared to be entirely made up and three others did not exist in the journals they were attributed to.
Several state counties, a nonprofit focused on sex education, and Planned Parenthood of the Heartland sued to get the grant solicitation paperwork restored to its original state, arguing that neither HHS nor the Executive Branch may rewrite mandates attached to money appropriated by Congress.
HHS decided that Teen Pregnancy Prevention money would fund only programs focused solely on abstinence and "body literacy," with education about contraception excluded.
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Evidence-backed comparisons of source perspectives and observed adoption signals. Read the methodology
Which Builder, Operator, and Investor concerns the observed source mix emphasized—not a truth score.
Evidence, demonstrated adoption, hype gap, incentives, and confidence are assessed independently, each on its own current evidence. How these are measured.
A quoted opinion, an unlinked docket
Nearly every hard fact traces to Judge Cooper's own words, quoted closely enough that the counts — two fabricated citations, three attributed to journals that never carried them — could be rechecked by anyone with the order in hand. Nobody in this reporting supplies the order: no case number, no filing date, no list of the seven studies, no HHS reply. And the AI attribution is the judge recognizing a pattern, not a finding about any specific tool or workflow.
A fingerprint, not a confession
No one in this reporting establishes that HHS ran a model. There is no procurement record, no vendor, no admission, no internal document — only a judge who thinks the citations smell synthetic and "wide speculation" about an earlier report. That is not enough to say how far AI drafting has spread through federal rulemaking, and a single injunction is a docket event rather than a measure of uptake.
The headline outruns the holding
Techdirt's headline has a court ordering HHS to stop using AI. The order does something narrower and, for a grantee, heavier: it freezes an abstinence-only rewrite as likely arbitrary and capricious, with the phantom studies serving as evidence that the agency did not reason its way to the policy. Our own framing carries a smaller stretch of the same kind — five bad citations out of seven is arithmetic on the judge's tally, not the result of anyone recounting the footnotes.
Adversarial record, partisan narrator
Everything factual here comes out of contested litigation at its earliest stage: Planned Parenthood of the Heartland and the plaintiff counties asked the court for precisely this conclusion, and HHS's account of its own citations appears nowhere. Techdirt makes no pretense of neutrality either — 'con-artists cosplaying as government officials' sets the register — though the invective sits on top of the quotations rather than substituting for them, which is the difference between slant and fabrication.
Verifiable in principle, unverified here
One outlet, one opinion, no second reader. The specificity helps — a named judge, his appointment year, exact citation counts, direct quotations — and each of those could be confirmed against the docket by anyone who bothered. Nobody in this coverage has, and the earlier HHS episodes are asserted without documents, so confidence sits where a well-quoted single source belongs: solid on what the judge wrote, thin on everything around it.