SOCIAL DETERMINANTS OF HEALTH, HEALTH SERVICE UTILIZATION
Bibliographic record
Abstract
Having the capacity to communicate in a common language is centrally important when people access and utilize health, social, and settlement services. While a considerable portion of recent immigrant women to Canada speak English or French fluently, many others do not command either official language fluently enough to access and utilize available health care services. In this qualitative study, data were collected with service providers who work with newcomer women, with women who became fluent in English after arriving in Canada, and with women who do not currently speak English. We report on the challenges women face in acquiring proficiency in English and, through the use of a social determinants of health framework, on how limited language skills negatively influence the health of these immigrant women and their families. We also present a number of strategies that health professionals could use to better support women’s attempts to ensure their health and that of their families. 1 We thank the participants who found time in their busy lives to participate in this study. We are also grateful for the support we received from our community partner, COSTI Immigrant Services. The funding from Canadian Council on
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".