Lessons learned, best practices and critical gaps in regional environmental assessment: A synthesis of Canadian and international literature
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Governments, industry, non-governmental organizations and the public increasingly view regional-scale environmental impact assessment as a viable means of understanding and proactively addressing cumulative environmental impact issues of proposed development programs, such as carbon emissions, biodiversity loss, habitat fragmentation and watershed pollution.<br/><br/>Regional assessment (RA) is a discretionary component of project-based impact assessment (IA) legislation in Canada. However, there is limited research on the scope of RA practice in Canada and elsewhere, or on identifying lessons to support RA implementation. Drawing on academic and grey literature published between 2000 and 2020, this project aimed to characterize RA practice. It also identified some emerging good practices to improve RA’s value to decision-making about natural resource development and conservation.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it