Health semiosphere in parks: case study in Quito and Madrid
Bibliographic record
Abstract
Introduction: The parks importance as green environments for healthy recreation is not assumed in their real dimension given their health benefits, although the World Health Organization recommends the availability of a minimum of 9 m2 of green space per person. Various international organizations recognize that the park's main essential services for communities are economic value, health and environmental benefits. Objective: To determine the health semiosphere in emblematic parks of Quito and Madrid. Methods: A mixed investigation was carried out using semiotics as the main tool. For the information gathering, the citizen survey technique of Quito and Madrid was applied, as a basis for a comparative analysis that allowed measuring the perception modes. Results: Intrinsic health activities were determined as part of the park's semiosphere, both in Quito and Madrid. In the first city, recreation was recognized as the main one, and sports in the second city; as well as cultural and recreational activities such as the relevant ones to be enhanced. Conclusions: The park's main activities are intrinsically linked to citizen's health, so their semiosphere is based on their determination with the aim of repowering them.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".