Adoption d’un nouveau cadre mondial pour la biodiversité : bilan critique de la COP 15
Bibliographic record
Abstract
The preparation of a new global framework for the post-2020 period occupied a central place in the intergovernmental negotiations on biodiversity from 2018 to 2022. The framework had to be adopted at the fifteenth Conference of the Parties (COP 15) to the Convention on Biological Diversity. This article presents a critical analysis of COP 15 based on a recount of past biodiversity governance initiatives at the global scale, a review of the negotiations held from 2018 to 2022, and a comparison of the expectations and results of the conference. The objective is to offer a critical appraisal of COP 15 based on interviews realized during and after the conference with experts and practitioners, as well as a review of the scientific literature and official documentation. The appraisal raises four main critics pertaining to the limits of the targets, governance tools, text clarity, and the approach to the new global framework. The results contribute to the reflection on biodiversity governance, the evaluation of international negotiations, and the discussions on the operationalization and implementation of the new global biodiversity framework.
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 | 0.089 | 0.095 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.056 |
| Scholarly communication | 0.025 | 0.012 |
| Open science | 0.004 | 0.012 |
| Research integrity | 0.013 | 0.019 |
| Insufficient payload (model declined to judge) | 0.002 | 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".