The Healthy Ageing/Vulnerable Environment (HAVEN) Index: Measuring neighbourhood age‐friendliness
Bibliographic record
Abstract
Abstract This study describes the development and testing of the Healthy Ageing/Vulnerable Environment (HAVEN) Index, a prototype composite spatial index for South Australia that reflects an area’s age‐friendliness. The index incorporates over 40 indicator variables across six variable themes: income and employment; education; health and housing; social connectedness; geographic access; and physical environment. Based on the deficit accumulation approach, the modelling uses area‐level rather than individual‐level data and is compiled through quantitative geospatial methods. Analysis using the HAVEN Index of state‐wide mortality data and hospital emergency department (ED) presentations for Central Adelaide found that vulnerable areas were associated with a higher risk of mortality and ED presentation. Comparisons between the HAVEN Index and a widely used national area‐level measure of socio‐economic differences found that the HAVEN Index compares favourably and provides additional information about local areas, which can inform needs‐based approaches to support the reduction of spatial inequalities and the development of age‐friendly neighbourhoods.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".