How to Achieve a Healthy City: a Scoping Review with Ten City Examples
Bibliographic record
Abstract
This scoping review of the literature explores the following question: what systematic measures are needed to achieve a healthy city? The World Health Organization (WHO) suggests 11 characteristics of a healthy city. Measures contributing to these characteristics are extracted and classified into 29 themes. Implementation of some of these measures is illustrated by examples from Freiburg, Greater Vancouver, Singapore, Seattle, New York City, London, Nantes, Exeter, Copenhagen, and Washington, DC. The identified measures and examples indicate that a healthy city is a system of healthy sectors. A discussion section suggests healthy directions for nine sectors in a healthy city. These sectors include transportation, housing, schools, city planning, local government, environmental management, retail, heritage, and healthcare. Future work is advised to put more focus on characteristic 5 (i.e., the meeting of basic needs for all the city's people) and characteristic 10 (i.e., public health and sick care services accessible to all) of a healthy city.
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.
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 | 0.008 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".