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
In this review, the authors examine the research evidence for the prediction of wife assault recidivism, lethal wife assault, and wife assault onset. They also review and present original data on the effect of treatment attendance on wife assault risk. Violence does not always become a stable habit, and variables associated with wife assault onset do not necessarily predict recidivism. General antisociality, psychopathy, substance abuse, and a history of assault and psychological abuse in the relationship are the most promising predictors of recidivism. Formal risk assessments, and victims' predictions, have demonstrated value in predicting recidivism. The authors review existing assessments for wife assault onset and recidivism and explain the relative merits of actuarial tools and structured clinical assessments. Because of statistical and practical limitations to predicting lethal assault, they recommend using an actuarial assessment of wife assault risk, plus attention to the strongest correlates of lethal assault when lethality is a concern.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
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