Bibliographic record
Abstract
Ce texte a pour but de clarifier les significations du concept de terrain, d’analyser son usage et de montrer les pièges que révèle une proximité non maîtrisée. En première approche, le terrain se donne à voir simplement dans sa matérialité. Il apparaît comme l’espace des pratiques quotidiennes, le lieu de l’expérience et l’école de la vie. Mais ce terrain n’est pas un absolu; il dépend de celui qui l’appréhende, de sa culture et de son histoire. À peine perçu, il est déjà construit, délimité, théorisé. L’article montre aussi comment s’articulent en France le travail deterrain, l’investissement sur le local et la démocratie de proximité. Aujourd’hui, le quartier sensible, comme espace emblématique de l’action publique en faveur des exclus, semble avoir laissé la place à une approche institutionnelle dont la référence serait le territoire. Le glissement du terrain au territoire souligne le passage d’une gestion des quartiers à une maîtrise des processus qui font de la mise à l’écart des uns la condition de la valorisation des autres.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.024 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".