How did the international year of biodiversity promote action at the national level
Bibliographic record
Abstract
One of the challenges faced by the United Nations in addressing global environmental issues is to find politically agreeable strategies that promote action at the national level. One approach is to designate observances, such as the 2010 International Year of Biodiversity (IYB). While the UN has used these international designations for several years, the results achieved from them are rarely examined, particularly at the national level. This research asked: How has the International Year of Biodiversity been used to initiate actions that protect biodiversity in Canada? It developed a case study, based on data collected from a documentation review, semi-structured interviews, and collaborative dialogues designed to further explore preliminary findings. Data were analysed qualitatively. Results converged around six findings, primarily around the Year's use as a communications tool. Ten recommendations aim to guide future uses of international designations in Canada as a tool to address global environmental issues.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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 teacher head, 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".