RISE: A Conceptual Model of Integrated and Restorative Elder Abuse Intervention
Bibliographic record
Abstract
Despite a growing number of elder abuse (EA) cases nationwide, response programs such as adult protective services (APS) lack a defined, prolonged intervention phase to address these complex situations. This article presents RISE, a model of EA intervention that works alongside APS or other systems that interact with at-risk older adults. Informed by an ecological-systems perspective and adapting evidence-based modalities from other fields (including motivational interviewing, teaming, restorative justice, and goal attainment scaling), the RISE model intervenes at levels of the individual older adult victim, individual harmer, their relationship, and community to address EA risk and strengthen systems of support surrounding the victim-harmer dyad. The RISE model addresses an intervention gap in existing systems to better meet the needs of EA victims and others in their lives, leading to more sustainable outcomes.
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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 | 0.009 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.015 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".