Immigrant Health Care Research and Knowledge Translation in Canada -- A Scoping Review
Bibliographic record
Abstract
Background: Canada receives 250000 new immigrants and refugees annually. One of five Canadians is immigrant. Immigrant health care research and knowledge translation are directly related to immigrant health and population health in Canada. Objectives: The study aims at identifying and mapping knowledge translation of immigrant health care research in Canada. Method:An exploratory scoping review was conducted to achieve the study objectives. The findings were synthesized with a narrative approach. Findings: The very limited immigrant health care research discoveries in very limited fields were generated incompletely to knowledge translation (5% and 3% respectively for knowledge translation rate and research-based integrated knowledge translation rate). Much less progress has been made in making available immigrant health care research evidence to inform the needs of health policymakers and stakeholders in Canada. Conclusion: Canadian immigrant health researchers, policy makers, stakeholders and knowledge-brokers should generate co-jointly immigrant health care research and effective and integrated knowledge translation. The funding agencies should provide much more support on the research and knowledge translation for the optimal improvement of immigrant health and population health in Canada.
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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 | 0.049 | 0.142 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.031 | 0.054 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.014 | 0.005 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".