Exploring Risk of Elder Abuse Revictimization: Development of a Model to Inform Community Response Interventions
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A focus of community-based elder abuse response programs (EARP), such as Adult Protective Services, is to reduce the risk of revictimization among substantiated victims. While elder abuse (EA) risk factor research has predominantly focused on understanding the risk of initial EA onset among the general older adult population, understanding of revictimization risk among substantiated victims is weak. This study sought to identify conditions that perpetuate EA among substantiated victims. Data were collected from multiple sources: focus groups with multidisciplinary teams ( n = 35), multidisciplinary team case revictimization risk evaluations ( n = 10), and reviewing a random sample of case records ( n = 250) from a large EARP in New York City. Sixty-two indicators of EA revictimization risk were identified across several ecosystemic levels: individual victim or perpetrator, victim–perpetrator relationship, and surrounding family, home, community, and sociocultural contexts. Findings carry implications for EARP practices to reduce EA recurrence and the development of measures to evaluate EARP intervention.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 it