The Vancouver Area Neighbourhood Deprivation Index (VANDIX): a census-based tool for assessing small-area variations in health status.
Bibliographic record
Abstract
OBJECTIVE: The Vancouver Area Neighbourhood Deprivation Index (VANDIX) is a census-based measure of socio-economic status (SES). It was designed to serve as an accessible and representative proxy marker of population health status without requiring more extensive health data. This paper describes the structure and previous applications of the VANDIX for measuring relative variations in health outcomes in British Columbia, Canada. METHODS: The VANDIX was constructed from a 2005 survey of provincial medical health officers asking them to comment on the best census markers of health status in British Columbia. The VANDIX is based on the weighted summation of seven socio-economic variables from the census, including in order of weighted importance: proportion without high school completion; proportion without university completion; unemployment rate; proportion of lone-parent families; average income; proportion of home owners; and employment ratio. RESULTS: The VANDIX has been applied in numerous research and policy settings across the province against several distributions of health status, including self-rated health, injury and access to health care services. In each assessment, the VANDIX has shown that socio-economic inequities parallel health inequities. CONCLUSION: SES is one of the most influential factors that shape population patterns of health outcomes. Census-based indicators of SES such as the VANDIX can serve as easily accessible and representative markers of population health status, and have application for policy, research and public health promotion.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".