2Canada and the Convention on Biological Diversity: Leadership Won and Lost
Bibliographic record
Abstract
The role Canada has played in relation to the Convention on Biological Diversity (CBD) illustrates a mixture of environmental vision and domestic constraints followed by an apparent inability to capitalize effectively on past leadership and by slightly two-minded policy initiatives. On the one hand, the Canadian contribution to the negotiation of the CBD was in many ways remarkable. On the other hand, Canada has lagged behind in implementing the accord and has since abandoned its role as leader—except in one or two issue-areas—to reach a nadir in 1999 when, prodded by the United States, it took the lead of the «Miami Group » in opposing a biosafety protocol that would put unacceptable constraints on the activities of its seed growers. From being a leader, Canada became a laggard and a blocker. This change of attitude in itself would deserve scrutiny. Numerous hypotheses could be advanced to explain it, from the personalities at the top of the Department of the Environment and the change of Prime Minister, to the fusion of foreign affairs and commerce into a single Department, the constraints of a federal system, the strength of domestic interests, and the absence of an overriding consensus around a core set of propositions and solutions to biodiversity-related issues. This section, however, covers a happier story, namely the contribution that Canada has made
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.027 | 0.015 |
| Scholarly communication | 0.018 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.009 | 0.011 |
| Insufficient payload (model declined to judge) | 0.019 | 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".