Bibliographic record
Abstract
En 2019, l’Assemblée générale des Nations Unies proclame la période 2022-2032 « Décennie des langues autochtones » en vue de préserver, de revitaliser et de promouvoir les langues autochtones, la plupart d’entre elles menacées de disparition.Non seulement l’extinction de ces langues mettrait en péril les cultures et les systèmes de savoirs auxquels elles appartiennent, mais elle engendrerait inévitablement un appauvrissement de la diversité culturelle sous toutes ses formes, portant ainsi atteinte au patrimoine commun de l’humanité.La Convention sur protection et la promotion de la diversité des expressions culturelles de l’UNESCO constitue un levier important pour l’adoption de politiques et mesures nationales destinées à promouvoir les expressions culturelles en langues autochtones. L’adoption de telles politiques et mesures est essentielle au respect des droits culturels des peuples autochtones reconnus dans les instruments de droits de la personne et la Déclaration des Nations Unies sur les droits des peuples autochtones.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 0.003 |
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".