Elder Abuse: A Global Challenge and Canada's Response
Bibliographic record
Abstract
Elder abuse is a global call to action. Nurses have a primary role to play in its detection and prevention. Globally, demographic change is creating an increasing number of older adults. Consequently, this increased number of people will be affected by age discrimination and ageism, both of which contribute to elder abuse. Despite the existence of the Universal Declaration of Human Rights, older adults are not recognized explicitly under the international human rights laws that legally oblige governments to address the rights of all people. Drawing initially on global conversations specific to elder abuse and the role of nurses, the current article explores the challenges of recognizing and combating elder abuse. To provide specific gerontological nursing strategies, recognition is given to actions implemented in Canada to address this major health challenge. The desired outcome is an advocacy framework for gerontological nurses to use in working toward the recognition and prevention of elder abuse. [ Journal of Gerontological Nursing, 48 (4), 21–25.]
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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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.032 | 0.009 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.004 | 0.012 |
| Research integrity | 0.016 | 0.016 |
| Insufficient payload (model declined to judge) | 0.012 | 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".