Sources of Data for Rural Health Research: Development of an Inventory of Canadian Databases
Bibliographic record
Abstract
Secondary data sources can often be used to help address questions about the health status, health behavior, health resources allocation, and utilization of health services of rural Canadians. But the task of deciding which Canadian databases are amenable to rural health research remains a challenge. As part of a larger research project titled "Canada's Rural Communities: Understanding Rural Health and Its Determinants," an inventory of 51 Canadian databases that have the potential of being used for rural health research was compiled, and it continues to be maintained and updated. The websites maintained by two of Canada's leading statistical data centers were systematically searched, along with other published articles and national reports, to produce this inventory. The criteria used to determine which data sources to include in this inventory are: (1) databases containing data at the national level that can be accessed by researchers, (2) databases containing data that are relevant to a variety of rural health issues, and (3) databases containing data that could be partitioned into rural and non-rural geographies. Detailed information is available by searching the inventory of national rural health research-related databases through the internet (www.cranhr.ca) or by contacting the lead author of this article. This article examines some of the issues in developing this resource and demonstrates the usefulness of its contents to Canadian and other rural health researchers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".