Older Women Speak About Abuse & Neglect in the Post-migration Context
Bibliographic record
Abstract
Elder abuse and neglect occur in every community and society. While considerable research is emerging on elder abuse, limited health science research exists to-date on older women experiencing abuse and neglect in the post-migration context in Canada. Building on our community partners’ interest in further understanding the topic of elder abuse and our previous work on violence against women throughout the migration process, this qualitative study explored older immigrant women’s experiences of and responses to abuse and neglect in one community. Data generation involved individual interviews and three focus groups with a group of older women (N=43) from the Sri Lankan Tamil community in Toronto. Findings show that older women experienced various forms of neglect and abuse and that the primary abusers were their husbands, children and children-inlaw. Their community and Canadian society at large were also implicated. Women’s responses to abuse were shaped by many factors at micro, meso, and macro-societal levels. In responding to abuse, older immigrant women showed remarkable resilience. Strategies are offered to better support older women’s attempts to cope with abuse and to promote their resiliencies.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.005 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.004 |
| 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".