TOWARDS HEALTHY URBAN DESIGN IN A RATIONALIST NEIGHBOURHOOD: A RESEARCH METHODOLOGY FOR THE MONTICELLI QUARTER IN ASCOLI PICENO, ITALY
Bibliographic record
Abstract
In 2012 the WHO's Lancet Commission made a study of potential and innovative associations among the themes of health, social equality, and economic development in urban planning.While recognizing the so-called "urban advantage" for health, the study affirmed that this advantage is not absolute, but is supported by long-term policies and good planning of the urban environment, with a concentration on projects on different scales that involve both the communities and different institutional levels.Some cities have accepted this challenge, trying to build a method to design/regenerate the city, placing health at the centre and involving local populations, various interest holders, and experts.Ongoing experimentation currently concentrates on two themes: methods of evaluating the state of health of cities and quarters and the identification of design proposals consistent with the objectives of health and well-being, which, based on the assessment process, can be improved and made more efficient.This contribution proposes a proper methodology for project assessment, currently in the first phase of experimentation, in the rationalist quarter of Monticelli in Ascoli Piceno (Italy).It is supported by some reference experimentation, including "GO! Utrecht" from the Netherlands National Institute for Public Health and the Environment, the Healthy Urban planning check list from the London Plan 2016, and some experiences developed by the City of New York (Active Design Guidelines, etc.).
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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 | 0.056 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.012 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".