The inclusion of men in domestic violence shelters: an everlasting debate
Bibliographic record
Abstract
Despite the fact that the inclusion of men constitutes a polarising issue that has created tensions and divisions throughout the history of domestic violence shelters, very little has been written on this issue. This paper specifically addresses this gap in the literature. Drawing upon the results of a doctoral thesis conducted with 48 advocates, the authors argue that the participants’ perspectives on the inclusion of men as workers or administrators in domestic violence shelters can be analysed from an axiological viewpoint. More specifically, the rationale underlying the participant’s position to support or to oppose men’s inclusion in shelters can be linked to core values underpinning shelters’ practices. This leads to three observations: 1) The inclusion of men clashes with a set of core values that guide the practices of participants who do consider the presence of men problematic; 2) Men are considered a positive addition in the shelters of participants who promote male inclusion, based on a different interpretation of similar values; 3) Men as ‘positive role model’, a crosscutting argument among those who promote their inclusion, is not related to any core values underlying shelters’ practices and raises two issues, which will be discussed in the paper.
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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 | 0.034 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.016 | 0.058 |
| Scholarly communication | 0.015 | 0.020 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".