Older Immigrant Access to Family Physicians in the Toronto CMA: A Mixed-methods Approach
Bibliographic record
Abstract
Ontario’s demographic structure is changing, and the senior population is expected to nearly double from 2020 to 2046 (2.6 to 4.5 million), leading to increased demand for healthcare services. Older immigrants are more likely to face spatial and aspatial barriers accessing healthcare. Spatial-quantitative analysis is used to explore the potential spatial accessibility to same-language family physicians (FP) for older Chinese immigrants living in the Toronto CMA. Enhanced 2-step floating catchment area (E2SFCA) modeling reveals areas with poor to very high accessibility. To gain a further understanding of spatial accessibility and use of care, survey data from older Chinese immigrants were analyzed to reveal individual experiences in accessing primary care prior and during the COVID pandemic. The study highlights the role of spatial access and other neighbourhood and individual characteristics in older immigrants’ access to health care services, as well as the value of integrating spatial analysis with empirical data in health care research involving older immigrants.
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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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".