An overview of Aboriginal health research in the social sciences: current trends and future directions
Bibliographic record
Abstract
OBJECTIVES: To examine if Aboriginal health research conducted within the field of social sciences reflects the population and geographic diversity of the Aboriginal population. STUDY DESIGN: Review. METHODS: We searched the Web of Science Social Science Citation Index, the Arts and Humanities Citation Index and Scholars Portal for the time period 1995-2005 using search terms to reflect different names used to refer to Canada's Aboriginal peoples. Citations that did not focus on health or Canada were eliminated. Each paper was coded according to 7 broad categories: Aboriginal identity group; geography; age; health status; health determinants; health services; and methods. RESULTS: Based on the 96 papers reviewed, the results show an under-representation of Métis and urban Aboriginal peoples. Most of the papers are on health status and non-medical determinants of health, with a particular focus on chronic conditions and life-style behaviours. Only 6 papers examined traditional approaches to healing and/or access to traditional healers/medicines. A small number involved the use of community-based research methods. CONCLUSIONS: Further research is required to address gaps in the current body of literature. Community-based research studies are necessary to address gaps that are most relevant to Aboriginal peoples.
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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 | 0.027 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.027 | 0.043 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 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".