The public health response to ‘do-it-yourself’ urbanism
Bibliographic record
Abstract
Greater understanding of the important and complex relationship between the built environment and human health has made 'healthy places' a focus of public health and health promotion. While current literature concentrates on creating healthy places through traditional decision-making pathways (namely, municipal land use planning and urban design processes), this paper explores do-it-yourself (DIY) urbanism: a movement circumventing traditional pathways to, arguably, create healthy places and advance social justice. Despite being aligned with several health promotion goals, DIY urbanism interventions are typically illegal and have been categorized as a type of civil disobedience. This is challenging for public health officials who may value DIY urbanism outcomes, but do not necessarily support the means by which it is achieved. Based on the literature, we present a preliminary approach to health promotion decision-making in this area. Public health officials can voice support for DIY urbanism interventions in some instances, but should proceed cautiously.
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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 | 0.013 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.029 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.007 | 0.008 |
| 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".