Seeking that "piece of paper" : an examination of protection orders under the Domestic Violence and Stalking Act of Manitoba
Bibliographic record
Abstract
Manitoba's Domestic Violence and Stalking Act was designed to provide victims with an opportunity to seek protective relief under civil law. Over its six-and-a-half year history, the Act faced criticism from those working in the field of domestic violence, who were concerned that protection orders were only being granted in approximately half of the applications made. The aim of this exploratory study was to empirically examine the factors which influence whether or not victims of stalking are successful in their attempts to obtain relief under the legislation. The dataset is comprised of the 483 protection order applications made in 2002 that contain evidence of stalking. Based on cross tabulation and logistic regression techniques, the analysis indicates that a number of factors influence the likelihood of an order being granted, including the sex of the applicant, evidence of threatening behaviours by the abuser, whether or not previous court orders exist between the parties, the presence of weapons, and the magistrate hearing the application. The present study situates civil protective relief within the theoretical debate over the wisdom of engaging the justice system in dealing with violence against women, and concludes with the assertion that civil orders are an important part of the overall response to this problem. The study also calls for future research to examine the impact of recent legislative amendments that are intended to broaden the range of situations in which protection orders can be granted under the Act.
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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 | 0.003 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.011 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".