Bibliographic record
Abstract
Introduction Identifying international EIA commitments as contributors to compliance suggests that EIAs can fulfill two primary functions in international environmental governance structures. In the short term, on a case-by-case basis, EIAs provide a process for facilitating the coordination of interests. Over the longer term, EIAs can have a more transformational role, shaping actor, including state, interests through the internalization of international environmental norms. These two functions are elaborated on in this chapter, with particular emphasis on the way in which internalization of international norms may occur within domestic EIA systems. Within IR scholarship, these two explanations, the first of which emphasizes interests, and the second of which emphasizes norms, as influencing state behavior, are often presented, at least as ideal types, as alternatives and in competition with one another. It is argued here with reference to EIAs that legal processes can be purposely structured to account for both material and ideational influences on actor behavior. Not coincidentally, this distinction between EIAs as interest-coordination mechanisms and EIAs as processes by which interests may be transformed also plays out in the domestic policy context. In the context of domestic EIAs, much of the focus on the interest-transformational aspect of EIAs has tended to look at whether individual EIAs can provide opportunities for social learning. The approach taken here looks at the transformational possibilities of EIAs from a more institutional and longer-term perspective.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.032 |
| Scholarly communication | 0.012 | 0.013 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".