Les enjeux des pratiques inclusives dans le domaine des loisirs. Du projet inclusif à la question des inscriptions sociales
Bibliographic record
Abstract
Inclusive practices in the area of recreation for children or adults with disabilities are one dimension of the collective commitment to a future society that would ideally be transformed into an “inclusive” society. Such a society should be able to ensure access to common social practices for all its members, regardless of their singularities, differences, and disabilities. But transforming high-performance, competitive, individualistic societies into inclusive societies is a paradoxical challenge, as Charles Gardou has already pointed out. As such, this inclusive project, insufficiently worked on and understood, can lead to a reproduction, or even a worsening, of situations of disability. How can we ensure that access to shared leisure spaces and ordinary leisure time practices for children, adolescents, or adults with disabilities is not limited to a tolerated co-presence with other actors? Leisure, as unconstrained time and free space, is particularly conducive to the inclusive project. The study of the forms and dynamics of sustainable social inclusion of people with dis/abilities in different leisure sport environments reveals some of the essential characteristics of inclusive leisure configurations: self-determination, gift-giving and reciprocity, plurality of experiences, and free and non-timed time.
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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 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.067 |
| Scholarly communication | 0.013 | 0.020 |
| Open science | 0.001 | 0.015 |
| Research integrity | 0.008 | 0.015 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".