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Record W2978191249 · doi:10.1080/07900627.2019.1662379

Governing international regime complexes through multi-level governance mechanisms: lessons from water, forestry and migration policy

2019· article· en· W2978191249 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Water Resources Development · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Development and Aid
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsCorporate governanceInternational regimeFragmentation (computing)International lawGlobal governanceBusinessPolitical scienceEnvironmental resource managementEconomicsLawEcologyFinance

Abstract

fetched live from OpenAlex

Why do international regime complexes develop? Are hard-law regimes effective in integrating regime complexes for international water resources management? Are there other alternatives? This article introduces international regime complexes and argues that these form a superior alternative to hard law and traditional global integrated regimes for many global policy issues. Failure of hard law to overcome fragmentation and generate integrated policy outcomes in international forestry, migration and water resource management is presented. Additional insights are drawn from two successful cases of water management in North America to argue for international regime complexes for better multi-level governance at the regional level.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.874
Threshold uncertainty score0.880

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.041
GPT teacher head0.314
Teacher spread0.272 · 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