Community Well-Being among the Registered Indian and non-Aboriginal populations in Winnipeg: Trends over time and spatial analysis
Bibliographic record
Abstract
The CWB Index has been developed to investigate well-being at the community level using census subdivisions to define the different types of communities. Because the basis for analysis is the entire population of a community, the presence of non-Aboriginal populations living in First Nations or Inuit communities, or of Aboriginal people living in “other” (non- Aboriginal) communities, has not yet been considered. Therefore, to date, the differences in well-being between Aboriginal and non-Aboriginal residents of the same areas have not been investigated at the community level. In addition, few (if any) CSDs identified as First Nations or Inuit are located in urban areas. There is a need to understand better the well-being of this segment of Canada’s population (Newhouse and Peters 2003). Thus the purpose of the present study was to apply the CWB Index to describe the socioeconomic well-being of Aboriginal and non-Aboriginal residents of the same urban centers. For this purpose, we use the city of Winnipeg in Manitoba, Canada as a “case study” because of its large Aboriginal population.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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".