Temps de pause et design de mobilier urbain pour les personnes a mobilite reduite
Bibliographic record
Abstract
Dans les politiques de la ville en France, les personnes à mobilité réduite font l’objet d’une attention particulière. Comment se rendre en ville, circuler, rejoindre différents bâtiments éloignés les uns des autres? Avancer dans l’espace est une condition essentielle de l’Homme, lui permettant de se déplacer, certes, mais aussi de rêver ou de réfléchir. Pour les personnes à mobilité réduite, aller d’un lieu à un autre étant difficile, la mobilité se réduit souvent à de petits trajets, dans des actions où domine l’obligation et non le plaisir. Avoir accès à l’espace urbain au sens large du terme, permettre aux individus de se déplacer librement en évoluant dans un environnement approprié représente donc un enjeu politique qui intéresse les sociologues, les urbanistes... et les designers. Cheminer implique non seulement d’avoir des lieux sans trop d’obstacles, mais également de pouvoir faire des haltes tout au long du parcours. L’étude présentée ici se penche sur la possibilité d’instaurer des repères fixes grâce à des lieux d’assise répartis dans l’espace de la cité afin que les personnes à mobilité réduite puissent non seulement se reposer, mais aussi procéder par étapes lorsqu’elles se rendent loin de chez elles et/ou dans des lieux différents. In urban political agendas in France, people with reduced mobility are given special attention. How can they get to the city, go around, and reach different buildings that may be far from each other? Moving around is an essential condition of mankind, which makes it possible to go somewhere, of course, but also to dream or reflect about things. For people with reduced mobility, moving from one place to another is difficult, and mobility is often reduced to small trips often dictated by obligation rather than pleasure. Having access to urban space in the broadest sense of the term, allowing individuals to move freely while at the same time evolving in an appropriate environment is therefore a political issue of interest for sociologists, town planners, and designers. Finding one’s way implies not only reaching places without encountering too many obstacles, but also being able to make stops all along the route. The study presented here examines the possibility of establishing fixed landmarks by means of seating spots distributed throughout the city so that people with reduced mobility can not only rest, but also proceed step by step going from one place to the next.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.026 | 0.005 |
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".