A Survey of Domestic Violence Perpetrator Programs in the U.S. and Canada: Findings and Implications for Policy and Intervention
Bibliographic record
Abstract
A 15-page questionnaire, the North American Domestic Violence Intervention Program Survey, was sent to directors of 3,246 domestic violence perpetrator programs (also known as batterer intervention programs, or BIPs) in the United States and Canada. Respondent contact information was obtained from state Coalitions Against Domestic Violence and from various government agencies (e.g., Attorney General) available on the Internet. Two hundred thirty-eight programs completed and returned the questionnaire, a response rate of 20%. The survey yielded descriptive data on respondent characteristics; program philosophy, structure, content, and service; client characteristics; treatment approach and adjunct services; and group facilitator views on intervention approaches and domestic violence policy and treatment standards. The programs varied in the extent to which they adhere to treatment approaches suggested by the empirical research literature. In addition, chi-square analyses were conducted on the associations between several factors. Significant correlations were found between respondent low level of education and adherence to a feminist-gendered program philosophy; respondent low level of education and use of a shorter assessment protocol; feminist-gendered program philosophy and incorrect facilitator knowledge about domestic violence; and feminist-gendered program philosophy and a program focus on power and control as the primary cause of domestic violence.
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.
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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".