Constructing a regional adolescent health and wellness index for British Columbia, Canada
Bibliographic record
Abstract
The purpose of this thesis is to construct an index of adolescent health and wellness for British Columbia, Canada, using the most recent available data. A three- round Delphi study is used in order to decide on what indicators to include in the index and each indicator’s relative weight. Spatial multi-criteria analysis (MCA) is utilized to combine the indicators into a single measure. The spatial MCA, technique for order preference by similarity to an ideal solution (TOPSIS) method was applied to the adolescent population as a whole and to examine male and female variation. This revealed that adolescent health and wellness is not experienced equally across the province. The Health Service Delivery Areas (HSDAs) Fraser South and Fraser North proved to have the greatest levels of adolescent health and wellness while the Northwest has the least. A rural/ urban gradient in adolescent health and wellness was revealed at the HSDA level. Male and female adolescents also experience health and wellness differently, with females achieving higher health and wellness across all HSDAs in the Province when directly comparing the two genders. The findings of this research are useful in informing discussions of resource allocation for reducing inequalities and inequities and in order to target future research.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".