Linking environmental and human health in English urban development decision-making: the human health literacy of environmental policy
Bibliographic record
Abstract
In this paper we provide an overview of the UK environmental regulatory framework for subnational policy and planning in devolved English urban areas based on a systematic coding of key legislation and policies against a matrix of sustainability attributes relevant for human health. Our findings suggest that while various elements of sustainability at diff erent scales are addressed to differing degrees, we need to move beyond the ‘three-legged stool’ of sustainability to assess linked environmental and societal health impacts. Assessing policy using a multifaceted lens of sustainability such as the one we propose can help to uncover health-development dependencies and the incentives and governance required to enhance these at diff erent scales (planetary, regional, neighbourhood and building). We propose a coordinative role for spatial planning to integrate responses to socio-environmental health priorities for sustainable development and make recommendations for dynamic decision-making on environmental and human health impacts in urban development settings. Doing so can help promote just (equitable) transitions, decoupled from a pervasive ecological modernization discourse that frames the political economy of planning at both the national and local levels.
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 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 | 0.020 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.017 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".