Characteristics of Elder Abuse Perpetrators by Sexual Orientation and Gender Identity of the Abused: Findings from the Canadian Longitudinal Study on Aging
Bibliographic record
Abstract
Lesbian, gay, and bisexual (LGB) older adults may be more vulnerable to elder abuse (EA) due to prior marginalization and trauma, lifelong discrimination, and health disparities. While characteristics of both victims and perpetrators can modify the risk for EA, few studies have focused on perpetrators. This study examined the number and type of perpetrator-victim relationships and perpetrator profiles for EA experienced in the prior year, by abuse type and sexual orientation and gender identity of the abused. Data are from community-dwelling Canadian Longitudinal Study on Aging participants aged 65 or older at follow-up 1 (n = 23,466). Heterosexual men and women reported being abused psychologically and physically most often by spouses or partners. Gay and bisexual (GB) men reported being abused psychologically most often by non-family, non-friend “others”. Lesbian and bisexual (LB) women reported psychological and financial abuse most often by siblings or other family members, and physical abuse by non-family, non-friend “others”. Heterosexual women were abused financially most often by their children, and both heterosexual and GB men reported more financial abuse by “others” or friends. Overall, 15% and 5% of participants reported abuse by multiple perpetrators of psychological and financial abuse respectively. LB women experienced more EA overall (18.8%), by multiple perpetrators (31% for psychological abuse, 66.5% for financial abuse) including by their siblings and other family members. These results have important implications for mitigation and preventive measures. They also highlight the need for further research concerning sexual minorities experiencing multiple abuse types and/or abuse by multiple perpetrators.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".