Targeting the transitions: applying stage-gate <sup>®</sup> thinking in strategic environmental assessment
Bibliographic record
Abstract
Strategic environmental assessment (SEA) practitioners have a tendency to emphasize assessment phases over the linkages between the phases. Explicitly addressing the transitions between stages could add rigour to SEA processes and make them more structurally robust. There is a considerable body of research on project management practices used by corporations during new product development (NPD). The stage-gate® model is presented as an example of a successful and innovative NPD approach that is frequently used by various industries, and which addresses the links between assessment phases. Stage-gate theory treats connections between project stages as gates which must be passed. The philosophy behind the stage-gate model is explored as a macro-process that could support current practices in SEA and other types of impact assessment. The stages and gates designed for a proposed Nova Scotia SEA framework are presented to show how stage-gate thinking can be adapted for use in SEA processes. The paper concludes that SEA processes could become more efficient and effective by integrating a philosophy of gated assessments.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.012 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".