Community Engagement in Environmental Assessment for Resource Development: Benefits, Emerging Concerns, Opportunities for Improvement
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
This paper discusses contemporary issues surrounding the efficiency of environmental assessment (EA) and the effectiveness of community engagement with focus on Canadian practice in the last two decades. Based on a review of the EA literature, we provide a brief overview of the benefits of effective engagement in EA processes. We then identify and discuss three enduring challenges to effective engagement amidst increasing pressures for a more efficient EA process, namely capacity, streamlining of EA processes, and the timing of EA and engagement in the resource development process. The paper concludes with key recommendations to ensure community engagement as a platform for enhancing increased inclusivity in environmental decision making. The paper is part of a special collection of brief discussion papers presented at the 2014 Walleye Seminar held in Northern Saskatchewan, which explored consultation and engagement with northern communities and stakeholders in resource development.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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