Students' Perceptions of Dangerousness to Public Safety of Paraphrases from the Koran, New Testament, Book of Mormon, Tibetan Book of the Dead, and Egyptian Book of the Dead Presented as Patients' Beliefs
Bibliographic record
Abstract
In one experiment 40 first-year psychology students were asked to judge dangerousness to society of 10 fictitious patients who professed beliefs about an "alien." The statements were actually paraphrases primarily concerning death and killing from the New Testament, the Koran, the Book of Mormon, the Egyptian Book of the Dead and the Tibetan Book of the Dead. In a second experiment 39 first-year psychology students were asked to rate the dangerousness of the verbatim statements with their sources identified. In the first experiment, statements from the Koran, which involved accessing a positive afterlife by killing nonbelievers in the name of a deity, were ranked as more dangerous. The differences between the sources accommodated 33% of the variance in the rankings for dangerousness. The group of students who were given the original statements and their actual sources ranked the statements from the New Testament and the Koran as significantly less dangerous than those who were told the statements were from patients. These results suggest that statements about killing and death may be rated as less dangerous if the person believes the source was a "sacred text."
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".