Bibliographic record
Abstract
Since the 1970s the issue of intimate partner violence (IPV) has been explained through the patriarchal desire of men to control and dominate women, but this gendered perspective limits both our understanding of IPV and its treatment. Intimate Partner Violence: New Perspectives in Research and Practice is the first book of its kind to present a detailed and rigorous critique of current domestic violence research and practice within the same volume. In this challenging new text, with contributions from the UK, the US, and Canada, the subject is assessed from a more holistic position. It provides a critical analysis of the issue of domestic violence including issues that are often not part of the mainstream discussion. Each of the chapters tackles a different area of research or practice, from a critical review of contemporary topics in domestic violence research, including a critical review of men's use of violence in relationships, a consideration of male victims, IPV within the LGBTQ+ community, perceptions of perpetrators and victims, and IPV within adolescent populations. The second half of the book examines challenges and opportunities for professionals working in the field and includes an analysis of an evidence informed perpetrator programme, the challenges faced working with male victims, and a discussion of the impact of domestic violence on children. Culminating with a series of evidence-based recommendations to bridge the divide between academic and practitioner stakeholders and to inform future working practices, this is an essential resource for students and practitioners alike
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.061 | 0.022 |
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".