Running Same-Sex Batterer Groups: Critical Refl ections on the New York City Gay and Lesbian Anti-Violence Project and the Toronto David Kelley Services’ Partner Assault Response Program
Bibliographic record
Abstract
Services for lesbian, gay, bisexual, transgender, queer (LGBTQ) partner abuse are needed and important. However, to successfully address the issue of LGBTQ partner abuse, communities need to take a two-pronged approach to this issue. First and foremost is the provision of services for victims and the families impacted by LGBTQ partner abuse in delivering a coordinated approach to intervening with this societal problem. The second prong of this approach involves addressing the abusive behavior of batterers. Services for LGBTQ partner abuse have been limited and primarily focused on victims. A cursory survey of the literature that we conducted confi rms this gap in service. The gap however, is even more pronounced when one considers the lack of research on batterers in LGBTQ partner abuse (Murray, Mobley, Buford, and Seaman-DeJohn 2008; Schwartz and Waldo 2004). Despite the limited research, batterer programs for LGBTQ abusers have developed in some major city centers across North America.
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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 | 0.025 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.008 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.007 | 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".