The integrity gap : Canada's environmental policy and institutions
Bibliographic record
Abstract
Figures and Tables Acknowledgments 1. Institutions and the Integrity Gap in Canadian Environmental Policy / Eugene Lee and Anthony Perl 2. How Canada's Stumbles with Environmental Risk Management Reflect an Integrity Gap / William Leiss 3. Canadian Environmental Policy and the Natural Resource Sector: Paradoxical Aspects of the Transition to a Post-Staples Political Economy / Michael Howlett 4. International Institutions and the Framing of Canada's Climate Change Policy: Mitigating or Masking the Integrity Gap? / Steven Bernstein 5. Energy Mixes and Future Scenarios: The Nuclear Option Deconstructed / Michael D. Mehta 6. Participatory Management and Sustainability: Evolving Policy and Practice in a Mountain Environment / Fikret Berkes, Jay Anderson, Colin Duffield, J.S. Gardner, A.J. Sinclair, and Greg Stevens 7. Policy Communities and Environmental Policy Integrity: A Tale of Two Canadian Urban Air Quality Initiatives / Anthony Perl 8. Integrity of Land-Use and Transportation Planning in the Greater Toronto Area / Richard Gilbert 9. Toronto's Exhibition Place: Closing the Integrity Gap between a Nineteenth-Century Fairground and a Sustainable Twenty-First-Century City / David Gurin 10. Conclusion / Anthony Perl and Eugene Lee Notes on Contributors Index
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.020 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.013 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.060 | 0.004 |
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".