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Record W2297972034 · doi:10.1017/cbo9780511494611.007

EIAs, interests and legitimacy

2008· book-chapter· en· W2297972034 on OpenAlexaff
Neil Craik

Bibliographic record

VenueCambridge University Press eBooks · 2008
Typebook-chapter
Languageen
FieldBusiness, Management and Accounting
TopicInternational Arbitration and Investment Law
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsLegitimacyPolitical scienceScholarshipCorporate governanceState (computer science)Law and economicsInternalizationIdeal (ethics)Compliance (psychology)Term (time)Public relationsSociologyBusinessSocial psychologyPsychologyLawComputer sciencePolitics

Abstract

fetched live from OpenAlex

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.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0040.032
Scholarly communication0.0120.013
Open science0.0010.006
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0080.001

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.

Opus teacher head0.027
GPT teacher head0.192
Teacher spread0.164 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2008
Admission routes1
Has abstractyes

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