The gender logic and effects of instrument mixes: implementing eldercare policy in Canada
Bibliographic record
Abstract
ABSTRACT Although policy instruments are often conceptualized as technical or neutral tools through which ideas and outcomes are connected, this article focuses on the discursive dimensions of policy instruments in Canada’s eldercare policy to explore their gendered and gendering logics and effects. Using frame analysis, we examine government acts, public reports and policy documents to uncover how different policy instruments at the federal and subnational levels frame caregiving and the caregiver. In doing so, we identify three distinct and contradictory frames – caregiver as resource, caregiver as worker and caregiver as autonomy – and illuminate their effects for gender equality outcomes. By looking at the implementation of eldercare policies in different provinces and across different government levels, we advance a better understanding of the gendered meanings and effects of instruments mixes.
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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 | 0.030 | 0.052 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.016 | 0.012 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".