ACHIEVING SUSTAINABILITY THROUGH LEGISLATION, PUBLIC INVOLVEMENT AND TRAINING
Bibliographic record
Abstract
The principle of Sustainable Development has been the basis of environmental policies and practices in the developed countries over the last few decades. In Canada, sustainability forms the basis of governance structure that is in place for the protection of the Great Lakes basin ecosystem. Along with the promulgation of a myriad of legislation and national and bi-national agreements, all levels of governments having jurisdictions have comprehensive public involvement and environmental training programmes in place to achieve sustainability for these very precious bi-national (Canada-US) natural resource. The article briefly describes this troika of measures, legislation, public involvement and environmental awareness training, which form the basis of means and methods employed to manage the Great Lakes and its ancillary resources. Of the three, the environmental awareness training of the decision makers in various governments in the Great Lakes watershed remains the important ingredient in the successes achieved to date. The International Navigation Association (PIANC) has also embarked on the journey to accomplish sustainability for its global membership, especially from the developing countries. The Environmental Commission (EnviCom) and the Commission for Cooperation (CoCom) of PIANC have undertaken to develop an environmental awareness training programme for the emerging economies. The article provides a description and status of PIANC’s environmental training programme. It concludes with a summary discussion of the pros and cons associated with the methods outlined for achieving sustainability for valued aquatic environments. The information here is primarily based on the experience of the author as a senior environmental manager for over two decades in the Canadian Government’s Ministry of Public Works and Government Services Canada (PWGSC), Ontario Region. Achieving Sustainability through Legislation, Public Involvement and Training
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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 | 0.019 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.014 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".