Evaluating Canada's compassionate care benefit: a geographic perspective
Bibliographic record
Abstract
Equity of access to health services is a main interest of health geographers.Recently, consideration has extended to policy-relevant analyses that forward spatial implications.In 2004, the Compassionate Care Benefit (CCB) was implemented to provide income assistance and job security to insured Canadians who take temporary leave from employment to care for a dying person.However, since it was introduced, uptake of the CCB has been significantly low.The development and implementation of a 'spatially informed' knowledge translation strategy can result in the identification of more efficient information-sharing pathways in order to increase needed awareness about the CCB, while examining how Canadians experience and understand the program across various geographic 'scales' assists with illuminating challenges and inequities to access.Such geographic perspectives contribute valuable knowledge to program evaluation, which, ultimately can better inform decision-makers on how to more effectively meet the needs of program users and other stakeholders.
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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 | 0.013 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.010 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".