A conceptual basis and methodological framework for regional strategic environmental assessment (R-SEA)
Bibliographic record
Abstract
The need to better assess and manage the cumulative effects of human development is well recognized; however, the practice of cumulative effects assessment has been constrained by the current project-based approach. Further, the broader regional and strategic frameworks designed to ensure a more proactive and futures-oriented cumulative effects assessment have, ironically, remained divorced from current practice and from each other. In response, in 2008, the Canadian Council of Ministers of the Environment and various federal and provincial agencies identified the notion of ‘regional strategic environmental assessment’ as a means to integrate the current silos of environmental assessment in Canada and improve the overall practice of cumulative effects assessment. In this paper we report on the ongoing initiative to advance regional strategic environmental assessment, and present a conceptual basis and methodological framework for its development and application.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.062 | 0.036 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.003 | 0.023 |
| Scholarly communication | 0.016 | 0.012 |
| Open science | 0.008 | 0.009 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".