Understanding the Trajectories of Women who use Violence Through an Intersectional Feminist Analysis
Bibliographic record
Abstract
This article discusses the results of a collaborative research project aimed at understanding the life trajectories of women who have self-identified as having used violence in a context other than self-defense, which is an understudied topic. Based on semi-structured interviews and aided by an intersectional feminist framework applied to life course theory, we present a qualitative analysis of 26 women's experiences of violence, precarity, and services. The three groups of trajectories are distinguished by level of precarity as determined by the experience of violence in childhood, socioeconomic and family contexts, criminalization, intensity of violence, and whether the women received adequate support. This shows (1) the need for interventions to prevent the reproduction or aggravation of violence suffered and perpetrated; (2) the importance of considering the inter-related factors (gender, class race, etc.) that contribute to the women's precarity; and (3) that these factors must be considered to understand the contexts in which women have come to use violence, without trivializing or excusing it, but rather properly situating it with a view to better preventing and intervening in these situations. Our recommendations are aimed at ensuring that social work practices do not contribute to the enforcement of punitive measures, but support women in pursuing their path.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".