Policies supporting informal caregivers across Canada: a scoping review protocol
Bibliographic record
Abstract
INTRODUCTION: As the population ages, governments worldwide have begun seeking ways to support informal caregiving. In this light, Canada is no exception, but despite the centrality of the informal care strategy in elder care, we know little about the intertwining and overlapping policies that have been implemented to support informal caregivers providing assistance to the elderly, and to fellow citizens with disabilities. This review aims to identify the diversity of Canadian national, provincial and territorial policies supporting informal caregivers. It seeks, from its generalist focus on all informal care, to draw out specific observations and lessons for the elder care policy environment. METHODS AND ANALYSIS: Given the vast and multidisciplinary nature of the literature on informal care policy, as well as the paucity of existing knowledge syntheses, we will adopt a scoping review methodology. We will follow the framework developed by Arksey and O'Malley that entails six stages, including: (1) identifying the research question(s); (2) searching for relevant studies; (3) selecting studies; (4) charting the data; (5) collating, summarising and reporting the results; (6) and conducting consultation exercises. We will conduct these stages iteratively and reflexively, making adjustments and repetitions when appropriate to ensure we have covered the literature as comprehensively as possible. We will pursue an iterative integrated knowledge translation (iKT) strategy engaging our knowledge users through all stages of the review. ETHICS AND DISSEMINATION: By adopting an iKT strategy we will ensure our knowledge users directly contribute to the project's policy relevant publications. Upon completion of the review, we will present the findings at academic conferences, publishing a research report, along with an academic peer-reviewed article. Our intent is to develop an online, free-access evidence repository that catalogues the full range of Canada's English language informal care support policies. Finally, the completed review will allow us to publish a series of policy briefs in collaboration with knowledge users illustrating how to promote and better implement informal care support policies. Our study has received ethics approval from the University of Calgary Conjoint Ethics Board.
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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 | 0.172 | 0.110 |
| Meta-epidemiology (narrow) | 0.004 | 0.006 |
| Meta-epidemiology (broad) | 0.009 | 0.007 |
| Bibliometrics | 0.025 | 0.025 |
| Science and technology studies | 0.011 | 0.007 |
| Scholarly communication | 0.013 | 0.006 |
| Open science | 0.008 | 0.008 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.042 | 0.009 |
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".