Health equity impacts of COVID-19 policies on dementia-relevant community services: A SGBA+ policy scan
Bibliographic record
Abstract
Abstract This presentation shares the methodology and early findings from a policy scan conducted to understand and assess the impact of COVID-19 policies on dementia care in the community for diverse populations in the province of Nova Scotia, Canada. The scan provided baseline information on: 1) Provincial legislative and regulatory policies related to dementia care in the community; 2) Orders and legislation enacted in response to COVID-19 that potentially impact those policies. Information was obtained from publicly accessible databases and government websites. Searches were also conducted using Google. 135 Acts were collected and reviewed. A specific aim of the scan was to generate knowledge about the impact of these layered policies in the context of a public health crisis from the perspective of local socially and geographically marginalized communities. A Sex and Gender Based Analysis Plus analytical approach was used to assess potential health equity impacts of COVID-19 policies on dementia care in the community. Information was organized using an adapted Health Equity Impact Assessment tool and Systems Health Equity Lens. Strengths and limitations of the approach and tools are discussed.
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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 | 0.017 | 0.043 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.015 | 0.028 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".