Contribution to the discussion on healthy cities: analysis of the correlation between the MHDI and the presence of public open spaces in the city of Recife/PE
Bibliographic record
Abstract
In Brazil there is an intuitive comprehension of the idea that open and green spaces affect the quality of life, but there are few effective correlation studies about the aspects that most contribute and support efficacious interventions in cities and their degree of relevance. In Europe and other countries, such as Canada, efforts have been made since the late 1980s to understand the contribution of these open spaces to quality urban living. Aiming to identify the intensity of this correlation in Brazil, and more precisely in Recife/PE, this paper explores the variables of the MHDI in different ways, as they relate to the concept of quality of life through the availability of public open spaces in the city. To support the study, a review of the literature about healthy cities, quality of life and open and green spaces was carried out, as well as an analysis of the available indexes that reflect the correlation of these concepts. As a result, the study identified a weak correlation between the MHDI variables and the presence of open spaces, including paved and green spaces; but also a better correlation when only the spaces with the largest vegetation coverage were considered. Finally, the study emphasizes the need to carry out new research based on other aspects of quality of life, in particular those related to health already contemplated in the international literature, to foster healthier cities in Brazil through a more efficient implementation of open space systems.
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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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".