Frozen text
The exact submitted article is preserved at intake so later edits do not change the object of study.
This independent study compares detector labels with documented writing workflows—not to ask whether prose looks machine-like, but whether the label readers see accurately describes how the work was made.
01 / The question
AI detectors evaluate features of finished text. They cannot observe who formed the argument, where a sentence came from, what an editor changed, or why the writer kept it.
This study places those two kinds of evidence side by side: the detector’s output and a contributor’s documented, post-specific workflow.
02 / What is compared
The exact submitted article is preserved at intake so later edits do not change the object of study.
The writer records what happened on that specific article, including whether AI flagged problems or supplied language.
Pangram’s label, score, flagged passages, scan date, and interface version are recorded without overwriting earlier runs.
The label is evaluated against documented provenance, with limitations and exclusion decisions retained.
03 / Commitments
04 / Initial cohort
The first phase is intentionally invitation-led. It begins with known contacts and writers who have already discussed their use—or non-use—of AI publicly.
Check eligibility“The study is not asking a detector to read a writer’s mind. It is asking whether the label shown to readers survives contact with documented provenance.”
05 / Study status
The full intake and analysis workflow will proceed only if a sufficiently trustworthy cohort participates. This recruitment gate is part of the protocol, not an afterthought.
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Expressing interest takes a few minutes. It is not consent to participate and does not require you to submit an article.
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