Intimate Partner Woman Abuse in Alberta's Child Protection Policy and the Impact on Abused Mothers and their Children
Bibliographic record
Abstract
The increased attention to children’s exposure to intimate partner violence has prompted child protection services (CPS) across the globe to make changes to their policies, including amending existing child maltreatment legislation and developing organizational policies in an attempt to protect children. Despite the well-intentioned nature of these efforts, they have been criticized for producing negative unintended consequences such as re-victimizing battered women, ignoring abusive men, and failing to protect children. To date, few studies have assessed the impact of these policy changes, especially from the standpoint of abused mothers. This article presents the results of a recent qualitative study that examined Alberta’s CPS policy and its impact on 13 abused mothers. Most of the women considered the involvement to be unhelpful, intrusive, and punitive. Many experienced tremendous feelings of grief and loss and felt that they had lost their identity as mothers, especially after their children were apprehended. Almost all of the women discussed experiencing greater levels of stress and anxiety, which frequently resulted in serious physical and mental health problems. Finally, the women reported that child protection involvement, most notably, apprehension of their children, had a damaging impact to their children.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".