Gender and dementia national strategy policymaking: Working toward health equity in Canada through gender-based analysis plus
Bibliographic record
Abstract
This article discusses the results of a content and critical discourse analysis of Canadian federal policy documentation relating to the development of a national Canadian dementia strategy. These documents span from 2013 and focus upon Canadian federal policy directives and directions up to the release, and including the release, of a national strategy in June 2019. The analyses, supplemented by a subtextual examination of these documents guided by Bacchi's (2012) "What's the Problem Represented to be?" framework, focuses upon the treatment of gender in policy documentation and the specific gender related policy framework, known as GBA+ (gender-based analysis and intersectionality), which is intended to bring about health equity to disadvantaged groups. As women, particularly, working class women and their carers, as well as women with additional intersecting factors, such as being lesbian or bisexual, are less likely to receive the dementia related care and services they need, precipitating a premature move to residential care, GBA+ is an essential policy framework in the attempt to address these inequities. However, findings point to a superficial treatment of gender, GBA and GBA+ in federal policy documents and lack a meaningful invocation of women's gendered and intersectional lived experiences of dementia. Additionally, the Canadian federal government's Dementia Strategy for Canada: Together We Aspire (2019) is grounded in a rendition of citizenship that do not work to unearth the complex relationships between citizenship, old age, gender and intersectional factors. As a result, the Dementia Strategy for Canada: Together We Aspire (2019) presents a version of citizenship that homogenizes older adults and prevents representations of older adults as diverse, complex and continually changing groupings. Therefore, inspired by Bartlett et al. (2018), I advocate for the application of a feminist and intersectional citizenship lens in Canadian federal dementia-related policymaking documentation going forward.
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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 | 0.021 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.054 | 0.035 |
| Scholarly communication | 0.028 | 0.007 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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".