Sustainable development and IIAs: from objective to practice
Bibliographic record
Abstract
The concept of “sustainable development” has been recognized by the world’s nations in a line of international documents and global events.1 While many have attempted to defi ne this term, 2 perhaps the most commonly accepted defi nition of “sustainable development” is the one proposed almost 25 years ago by the Brundlant Report, in which it was described as “[D]evelopment that meets the needs of the present without compromising the ability of future generations to meet their own needs.”3 In essence, the ultimate objective of sustainable development is the integration of economic development with environmental protection and social well-being.4 Sir Elihu Lauterpacht has recently explained in this respect: “Sustainable development, therefore, represents a commitment to a different kind of economic development, one that focuses on achieving important improvements in the opportunities and quality of life without jeopardizing the interests of future generations.” 5 Associate Professor, Faculty of Law, Civil Law Section, University of Ottawa. With special thanks to Erika Arban and Misha Benjamin for invaluable research assistance.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.020 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.010 |
| Insufficient payload (model declined to judge) | 0.013 | 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".