Bibliographic record
Abstract
Intimate partner violence (IPV) is a considered one of the most pervasive forms of gender-based violence. In Canada, approximately 4% of Canadians report severe forms of IPV, such as being physically, sexually, or emotionally victimized by their partner. That said, these rates are a drastic underrepresentation of the true rate of IPV that is not reported to the police, including violence within same-sex relationships. Statistical data indicates that those in gay, lesbian, or bisexual relationships are more likely to be victims of violent crimes such as IPV relative to those in heterosexual relationships. Further, public surveys indicate that members of same-sex couples often refrain from reporting IPV due to threats related to their sexual identities. Research also has demonstrated that our perceptions of violence are moderated by extralegal factors, such as sexual orientation. Specifically, violence against women is viewed as more severe and taken more seriously by the criminal justice system than violence against men, across both same-sex and opposite-sex relationships. As such, the seriousness and criminal justice response to IPV incidents may be minimized or misinterpreted based on views about sexuality and gender identity, as well as levels of homophobia. Given that pre-existing biases and beliefs can lead to judicial bias concerning judgments of severity, culpability, and blame, this study was designed to examine how views concerning sexual orientation, use of threats, and instigator gender influence judgments of IPV. Faculty Mentor: Kristine Peace Department: Psychology
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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.410 | 0.221 |
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".