Beyond Indicators and Reporting: Needs, Limitations and Applicability of Environmental Indicators and State of the Environment Reporting
Bibliographic record
Abstract
This research examines the perceptions and use of environmental indicators and state of the environment reports by local government and Conservation Authority decision makers and practitioner’s within the Ontario portion of the Great Lakes and St. Lawrence basin. Participants describe their information needs and how indicators and SOER are used at the local level; and what limitations or challenges they face to bridge the gap between monitoring information and policy. A multi-method approach including a web-based survey and follow-up telephone interviews was the primary data collection method used. Indicator and SOER knowledge and information are further explored to determine information exchange amongst different levels of governance. To review the dissemination of indicator and SOER information from a higher spatial scale down to the local level, the State of the Great Lakes environmental indicators and SOER, developed by the governments of Canada and the United States served as a case study.
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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 | 0.211 | 0.383 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.016 |
| Science and technology studies | 0.005 | 0.012 |
| Scholarly communication | 0.017 | 0.023 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".