The Healthy Ageing/Vulnerable Environment (HAVEN) Index: Measuring neighbourhood age‐friendliness
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.015 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it