Promising Practices of Nonprofit Organizations to Respond to the Challenges Faced in Countering the Mistreatment of Older Adults
Bibliographic record
Abstract
Abstract This article discusses promising practices used by employees and volunteers in nonprofit organizations (NPOs) in countering the mistreatment of older adults (CMOA). The findings presented here are the result of research on the material and financial actions of NPOs in CMOA, based on multiple case studies in five active Canadian NPOs in the framework of CMOA. The body of data comprises organizational documentation from NPOs, socio-demographic questionnaires and group or individual interviews with 64 participants (management volunteers, employees, field volunteers and accompanied older adults). Themed intra- and intercase analyses were carried out. Some key challenges faced by the active NPOs in CMOA include the continuity of follow-ups, difficulty in reaching older adults and obstacles to requesting help. Promising practices that have been implemented to contribute to the response to these challenges, such as collaboration practices, proactive prevention activities, canvassing and shelter services, are considered.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".