A DECISION-MAKER'S TOOL FOR SUSTAINABILITY-CENTRED STRATEGIC ENVIRONMENTAL ASSESSMENT
Bibliographic record
Abstract
This paper outlines a Decision-Maker's Tool (DM Tool), designed to guide practitioners and their inter-disciplinary teams through a typical strategic environmental assessment (SEA) process. While SEA properly includes post-decision follow-up, the DM Tool covers the SEA process up to the creation of a Briefing Note for the decision maker. Together, use of the DM Tool and the Briefing Note should facilitate positive contributions to sustainability through well considered and aligned policies, plans and programmes (PPPs), by enhancing the comprehensiveness, consistency, clarity, accessibility and credibility of decision making information. The discussion presumes that the SEA is central to the PPP development process, rather than being a separate exercise. The DM Tool and Briefing Note are designed to recommend PPP action based on clearly stated needs and purposes, addressing the key issues, and application of explicit sustainability criteria in the comparative evaluation of feasible alternatives. Particular attention is paid to recognising trade-offs and residual risks, and presenting all this information concisely for the decision maker.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".