Objectified knowledge and abstracted discourse: Excluding abused women's lived realities from Canadian child custody law
Bibliographic record
Abstract
Research into abused women's experiences of the family law system reports that they experience a profound sense of betrayal, as they disclose intimate violence to various professionals. Consistently, these studies show that women's revelations are distorted and minimized in custody negotiation processes and then ignored as women are pressured to accept difficult and, at times, dangerous custody arrangements. These experiences occur fundamentally because the system is permeated with objectified knowledge and particularized discursive meanings and images about high conflict violence, abused women, children's best interests, and the 'proper' family. This dissertation presents the findings of an institutional ethnography of abused women's experiences of custody negotiation. Data were collected through 32 in-depth interviews with abused women of differing social locations, women's advocates, family law lawyers, and child custody mediators and assessors. The analyses document how women's experiences of intimate relationship violence---fear, isolation, pain, and anger---become inserted into, altered, and silenced by disciplinary knowledge---the standardized, official accounts produced by policy, institutional, and professional discourses and practices. Interviews with professionals revealed how their routine and mandated practices altered women's stories, so that these are hearable within the system. The thesis concludes by discussing the implications of the findings for professional practice, policy, and research.
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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 | 0.009 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.050 | 0.070 |
| Scholarly communication | 0.021 | 0.009 |
| Open science | 0.003 | 0.018 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".