Female Perpetrators of Intimate Partner Violence
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
The literature on intimate partner violence (IPV) has primarily focused on male perpetrators. Crime statistics and empirical research have shown that females also perpetrate violence against their partners. This presentation investigates the offence, perpetrator, and victim characteristics, as well as the prevalence of risk factors observed in a sample of 45 females who have perpetrated IPV and a matched sample of 45 males (based on age and prior criminal history). Data were obtained from a local police-reported domestic violence sample. The matched group did not differ in risk scores on two measures of IPV risk for recidivism, but had notable differences regarding the use of threats, weapons, and confinement at the index occurrence. Also, demographic differences emerged between the groups regarding their employment status, nature of their criminal histories, and their victims. Implications of these findings will be discussed with regards to identifying gender-specific differences when applying the RNR principles to female IPV perpetrators. Discipline: Psychology Faculty Mentor: Dr. Sandy Jung
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 | 0.001 |
| 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 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| 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