GOVERNING INFORMATION: A THREE DIMENSIONAL ANALYSIS OF ENVIRONMENTAL ASSESSMENT
Bibliographic record
Abstract
This article examines the institutional, political and regulatory dimensions of environmental assessment (EA) processes. While EA is most often conceptualized as a regulatory instrument, this article contends that viewing EA in this narrow fashion obscures the broader implications and significance of EA as a distinct form of governance. When conceived as a mode of governance, EA varies considerably in terms of the key governance characteristics emphasized in this symposium. The empirical evidence rests upon three cases studies looking at very different multi‐level governance contexts: the Tamar Valley Pulp Mill in Australia, the Whites Point Quarry in Canada, and the Byströe Canal Project in the Ukraine. The case study analysis identifies large variations in the institutional, political and regulatory form that EAs take, indicating that approaches identifying EA as a form of ‘New Governance’ are overly simplistic. The analysis also points to the multi‐directional influence of different governance dimensions. The insights derived from the use of the three dimensional framework validate its value as an analytical tool.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.014 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".