Stories of resident-to-resident aggression: Fears and experiences in long-term residential care
Bibliographic record
Abstract
This thesis explores family caregiver concerns and experiences around resident-toresident aggression (RRA) in long-term residential care (LTRC).Canadian media reports spanning a ten-year period (2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016)(2017) about RRA (n= 64) were analyzed with a critical discourse lens to examine the representation of family members.Also, family caregivers of residents in LTRC from two British Columbia health regions (n= 8) were interviewed about the influence of RRA media reports on perception of safety for themselves and their relatives in LTRC, and their broader caregiving experiences.Family caregivers viewed media reports on RRA as sensational, contributing to the stigma of dementia, and lacking context, but they did not impact the family caregivers' sense of safety.Instead, the lack of access to empowerment structures (i.e.informal power, formal power, information, support, and education) and the ambiguous position of family within the hierarchical power structure of LTRC negatively influenced their caregiving experiences.Findings suggest a need for systemic change to increase family empowerment and role clarity with respect to prevention and management of RRA.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.008 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".