Le <i>Cadre mondial de la biodiversité de Kunming-Montréal</i> : vers une nouvelle stratégie de mise en oeuvre de la <i>Convention des Nations Unies sur la diversité biologique</i>
Bibliographic record
Abstract
La Convention des Nations Unies sur la diversité biologique est une convention-cadre dont le contenu dégage des principes généraux sur l’utilisation durable de la biodiversité, sa conservation ainsi que l’accès aux ressources génétiques. Afin d’appliquer la Convention sur cet enjeu transfrontière, global et transversal, les États se réunissent au sein de leur Conférence des Parties pour adopter des plans stratégiques et des actions concertées. Les dernières stratégies, notamment le Plan stratégique pour la diversité biologique 2011-2020 et les Objectifs d’Aichi n’ont pas permis d’atteindre les cibles fixées. À l’occasion de la quinzième Conférence des Parties, les États ont adopté le Cadre mondial de la biodiversité de Kunming-Montréal s’étalant de 2022 à 2030. Cet article brosse le portrait de l’échec des premières stratégies et soulève les éléments qui distinguent la dernière stratégie des premières, qui se fonde sur la théorie du changement et sur l’urgence de la crise de la perte de biodiversité.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 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".