Implicit associations in self -injurious behavior: An evaluation of the mechanisms involved in the affect -regulation model
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
This study evaluated the self-punishment hypothesis and the distraction hypothesis of the affect regulation model of self-injurious behavior (SIB) using the R-COPE, the Implicit Association Test (IAT, Greenwald, McGhee, & Schwartz, 1998) and the Toronto Alexithymia Scale (TAS-20, Bagby, Parker, & Taylor, 1994a). Data were collected from 62 undergraduate students, 33.9% of the sample engaged in SIB. Using the IAT, participants in both groups had positive self-concepts, which challenges the self-punishment hypothesis. IAT data did not support the distraction hypothesis. When a higher cut-off score for the SIB group was used, avoidant and self-punishment as coping strategies, as well as, alexithymia were endorsed at significantly higher rates in the SIB group. The IAT findings indicate that stable automatic associations do not underlie self-punishment and distraction. It is proposed that these mechanisms are more appropriately understood as being activated by negative affect.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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