Ethical and Psychosocial Issues Raised by the Practice in Cases of Mistreatment of Older Adults
Bibliographic record
Abstract
Intervention regarding older adult mistreatment raises many questions for practitioners. They have to interact with the victim, the abuser, and, in many cases, with both of them at the same time. In such cases, five themes emerge from the literature review on psycho-social and ethical issues in practice: practitioners' pre-construction and axiological frameworks, victims' capacity, confidentiality versus collaboration between practitioners or between agencies, social and family responsibilities and the balance between competing values in practice. Practitioners are well placed to offer a critical reflection on their practice and on ways of improving it. The goal of our qualitative study is to identify issues and ethical dilemmas in elderly mistreatment situations as represented in the discourses of practitioners in reference to interventions in their psychosocial practice. Sixteen practitioners from the public and community (non-profit organization) sectors were interviewed using a practice history approach. This paper presents the main ethical and psychosocial issues raised by practitioners and some ideas to improve the practice. It is motivated by the crucial question haunting the practitioners' minds: "How far should we go?"
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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 | 0.044 | 0.094 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.016 | 0.030 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.007 | 0.006 |
| 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".