Three Values That Should Underlie Community-Based Dementia Care Strategies
Bibliographic record
Abstract
To guide action towards a community-based dementia care strategy, Morton-Chang et al. provide the following three key strategic pillars: putting people with dementia first, supporting informal caregivers and enabling local communities to support people with dementia. While, in principle we agree with these pillars, the ways in which we interpret and implement them differ. We propose three values that should underlie any discussion of dementia policy, strategy and change and that place people with dementia at the heart of these discussions: that of the rights of people with dementia, of diversity and equity, and inclusion.
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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 | 0.089 | 0.095 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.026 | 0.106 |
| Scholarly communication | 0.027 | 0.029 |
| Open science | 0.007 | 0.024 |
| Research integrity | 0.083 | 0.097 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".