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
Research has demonstrated that psychopathic traits are associated with risk taking spread across a variety of domains. One domain concerns sexual risk-taking, usually conceptualized as unsafe sex and promiscuity. However, psychopaths also may engage in sexual violence, including the use of coercive tactics in order to obtain sex. The present study was designed in two parts (counterbalanced) to further our understanding of the relation between psychopathic traits and sexual coercion. Part 1 will investigate the association between psychopathic traits, sexual risk, and use of both overt (e.g., using physical force, use of drugs or alcohol) and covert (e.g., massaging, sweet talking, guilt-tripping) sexual coercion strategies. Part 2 will examine whether psychopathic traits alter perceptions of sexual coercion. In particular, participants will be presented with a vignette that varies according to the level of sexual coercion (low/high), type of sexual coercion (verbal/physical/both), and whether sexual consent was granted following the use of these strategies or not. Following the vignette, participants will be asked to complete a judgment questionnaire concerning perceptions of consent, level of violence/coercion, criminal culpability, guilt, and sentencing severity. We predict that psychopathic traits will be associated with greater endorsement of use of sexual coercion, and a response pattern that indicates minimization of violence and blame for the vignettes. Faculty Mentor: Kristine Peace Department: Psychology (Honours)
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.020 |
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