Generating effective global environmental governance: Canada's 2002 challenge
Bibliographic record
Abstract
The international community has been generating international environmental institutions at the bilateral, regional, plurilateral, and global level for well over a century, with a notable increase since the UNCED Rio conventions of 1992.Yet as Canada and its global partners confront such critical twenty-first century environmental challenges as fulfilling their climate change commitments, and forging new conventions on forests and freshwater, there is considerable doubt about the comprehensiveness, coherence and effectiveness of the cumulative assemblage.How can Canada best lead in generating effective global environmental governance?As globalization generates intensifying national vulnerability, the result is increasing, integrated, potentially irreversible global ecological stress.To meet this urgent challenge, the existing array and approach of incremental, fragmented and fragile environmental institutions offers an inadequate global environmental governance response.Among the available alternative approaches, only the construction of an overarching powerful World Environmental Organization, as powerful as the WTO for trade and the IMF for investment can generate a comprehensive, coherent and effective answer.Canada's ecological vulnerabilities create a catalyst for it to lead in the creation of such and organization, while its broad array of capabilities suggest carefully-crafted Canadian leadership can be effective in realizing such an admittedly ambitious project.In the aftermath of the September 11 terrorist attacks, Canada's hosting of the G20 in Ottawa in November 2001, the G8 in Kananaskis in June 2002, and the preparatory process of for the Word Summit on Sustainable Development give it the opportunity to lead in the creation of such an organization as the centerpiece deliverable of that Summit in September 2002.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.018 | 0.008 |
| Scholarly communication | 0.015 | 0.003 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.017 | 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".