Preventing intimate partner violence: a formative evaluation of an intervention programme serving immigrants, refugees and visible minority men
Bibliographic record
Abstract
Although intimate partner violence (IPV) is the leading type of violence experienced by women in many parts of the world, limited research with mixed findings exists on IPV intervention programming for immigrants and visible minority subgroups. Changing Behaviors is an eight-week IPV intervention programme targeting immigrants, refugees and visible minority clientele in British Columbia, Canada. This pilot study provides a preliminary examination of programme impacts, using a mixed methods pre-test/post-test design. Fourteen participants completed the psychological and physical abuse subscales of the Abusive Behavior Inventory (Shepard and Campbell, 1992), and 11 participants answered open-ended questions concerning knowledge and skills learned in the programme. Participation in Changing Behaviors resulted in marginally significant decreases in psychologically abusive behaviours, but no change in physical abuse or gains in knowledge and skills concerning anger reduction or healthy emotional expression. Future attainment of gains in skills and reductions in abuse may be more successful through incorporating additional culturally enhanced components into the programme curriculum, as well as adding evidence-based practices from the IPV intervention literature.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".