Reflections on the Consideration of Greenhouse Gas Emissions in Environmental Impact 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
Abstract Environmental impact assessment ( EIA ) involves assessing the implications of proposed activities on the environment to inform decisions about whether those actions should proceed and under what conditions. Efforts are being made to incorporate climate change considerations into EIA internationally, but the assessment of greenhouse gas ( GHG ) emissions poses particular challenges. This article compares the incorporation of GHG emissions into EIA in two jurisdictions: Canada (under the Impact Assessment Act 2019) and Western Australia (under the Environmental Protection Act 1986). Four questions are considered, relating to screening and scoping; information requirements; decision-making and condition setting; and post-approval activities. Key differences between the two jurisdictions were found in relation to screening and scoping (Western Australia applies an emissions threshold while Canada utilizes a project list coupled with tailored guidelines); decision-making (Western Australia generally considers a straight line trajectory to net zero by 2050 as acceptable whereas Canada considers emissions in the context of international commitments and against other sustainability considerations); and post-approval activities (a strength of the Western Australian system is mechanisms enabling review and tightening of GHG conditions over time). It will be important to continue to review the effectiveness of EIA as a tool for climate mitigation as practice evolves.
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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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