Bibliographic record
Abstract
Le savoir expérientiel est l’argument phare contemporain justifiant le recours à un nouveau type d’acteur – le pair – dans les champs du handicap, de la santé mentale, de la maladie chronique, mais aussi des addictions, de la grande pauvreté ou encore des troubles neurodéveloppementaux. Cet article vise à comprendre et à définir le concept de savoir expérientiel. La méthode employée pour ce faire est constituée en deux temps. Tout d’abord, une courte recension de la littérature permet de situer ce concept dans son contexte d’émergence. Les débats autour de sa validité scientifique ou encore de sa légitimité au nom de la démocratisation de nos sociétés sont ainsi éclairés. Ensuite, une analyse des propositions théoriques de Thomasina Borkman - auteure à l’origine de ce concept - et leur critique partielle permettent de fonder un argumentaire rationnel mettant en avant la question de l’intersubjectivité, menant à la caractérisation des différentes dimensions du savoir expérientiel et à sa définition.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.026 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".