(Re)-discovering rivers benefits in the City: a One Health approach
Bibliographic record
Abstract
Abstract In the context of climate change and increasing urbanization, urban bathing is emerging in France and elsewhere, thus bringing us to question how we can maximize the benefits for the health of populations and minimize the risks. The multidisciplinary URB-bain project studies the feasibility of bringing bathing back to the urban environment. In a One Health approach, it combines 1/ the study of health risks associated with the chemical and microbiological analyses quality of the water of two potential bathing sites (Metz, France) and 2/ a socio-historical and political approach to the use of urban bathing in France, Europe, and Canada. This paper will present the first results of axis 2. Two types of qualitative data were collected: semi-structured interviews and documentation. Interviews were conducted with technicians, decision-makers, and NGOs. Eighteen interviews were performed (10 in Metz, France, 3 in Paris, and 5 in Quebec, Canada), recorded, transcribed, and analyzed (N'Vivo 12©). Other sites were documented (Copenhagen, Berlin). The causality model between urban bathing and health developed within the framework of the project and the principles for operationalizing the One Health concept (collaboration, coordination, communication, capacity building) guided the analysis. Documentation analysis showed a renewed interest in urban bathing in France since the 1990s, culminating in 2017 in Paris with the opening of a pool in the Canal de la Villette under pressure from citizens and motivated by the hosting of the Olympic Games in 2024. In France, health considerations focused on regulatory issues based on bacteriological quality for the institutions. The water bodies’ ecological and chemical status is neither a concern nor a One-health approach. Social accessibility and gender equity in the public space are important issues. The analysis of the interviews, still in progress, will help to put the initial results into perspective with the other sites studied. Key messages • Urban bathing is a public health issue in a context of climate change. • Urban bathing is a one-health issue.
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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 | 0.018 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.007 | 0.027 |
| Scholarly communication | 0.015 | 0.012 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.004 | 0.004 |
| 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".