Articulation entre éducation et citoyenneté au Brésil : entre discours prescriptif et discours scientifique
Bibliographic record
Abstract
Comment l’éducation et la citoyenneté s’articulent-elles au Brésil? Cette question est explorée à travers une analyse de contenu des documents officiels, juridiques et curriculaires brésiliens, ainsi qu’une analyse lexicométrique (via Iramuteq) d’articles scientifiques publiés au Brésil. L’objectif de cet article est de mettre en lumière les thématiques de convergence et de divergence entre les sphères prescriptives (loi et curricula) et scientifiques concernant la relation entre éducation et citoyenneté. Il en ressort que ces deux domaines demeurent autonomes. D’une part, les documents juridiques et curriculaires promeuvent une vision idéale, où l’éducation et la citoyenneté sont deux éléments indissociables d’un tout. D’autre part, les articles scientifiques traitent de l’éducation à la citoyenneté en lien avec d’autres thématiques et institutions, dépassant ainsi le seul cadre scolaire. Enfin, l’ensemble des documents du corpus met en avant la reconnaissance de la diversité socioculturelle comme un pilier central de l’éducation et de la citoyenneté au Brésil.
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 | 0.011 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.006 | 0.017 |
| Scholarly communication | 0.014 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 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".