GOVERNING INFORMATION: A THREE DIMENSIONAL ANALYSIS OF ENVIRONMENTAL ASSESSMENT
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 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.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.012 | 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