Trigger Warnings Are Trivially Helpful at Reducing Negative Affect, Intrusive Thoughts, and Avoidance
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Students are requesting and professors issuing trigger warnings—content warnings cautioning that college course material may cause distress. Trigger warnings are meant to alleviate distress students may otherwise experience, but multiple lines of research suggest trigger warnings could either increase or decrease symptoms of distress. We examined how these theories translate to this applied situation. Across six experiments, we gave some college students and Internet users a trigger warning but not others, exposed everyone to one of a variety of negative materials, then measured symptoms of distress. To better estimate trigger warnings’ effects, we conducted mini meta-analyses on our data, revealing trigger warnings had trivial effects—people reported similar levels of negative affect, intrusions, and avoidance regardless of whether they had received a trigger warning. Moreover, these patterns were similar among people with a history of trauma. These results suggest a trigger warning is neither meaningfully helpful nor harmful.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it