TYPOLOGIES OF ELDER ABUSE IN BRAZIL
Bibliographic record
Abstract
situations toward urban community-dwelling older women by male family members (i.e., adult child or spouse). Multiple types of abuse were committed toward each victim, but financial abuse was most typical. Shared living arrangements and social isolation and a lack of social supports contributed to environmental risk factors; perpetrator risk factors included financial or housing dependence on the victim, behavioral problems, and salient barriers to provide care (e.g., recent decline in health status, lack of knowledge, burden). Victims were at risk when experiencing physical impairment or disability or financial dependence/low-income. In two of the cases, healthcare professionals identified the occurrence of abuse. Likely interventions for the victim include counseling, health care, legal assistance, social and supportive services, and support groups. For the perpetrator, suggested interventions included counseling, remedial services (including alternative housing, employment services, and caregiver intervention).
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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 | 0.000 |
| Science and technology studies | 0.000 | 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".