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Record W2311479810 · doi:10.1093/publius/pjw002

Governing an International Transboundary River: Opportunism, Safeguards, and Drought Adaptation in the Rio Grande

2016· article· en· W2311479810 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

VenuePublius The Journal of Federalism · 2016
Typearticle
Languageen
FieldEngineering
TopicWater resources management and optimization
Canadian institutionsMcMaster University
Fundersnot available
KeywordsOpportunismEconomic shortageCorporate governanceWater scarcityAdaptation (eye)GeographyPolitical scienceEnvironmental resource managementEnvironmental planningBusinessGovernment (linguistics)EconomicsLaw

Abstract

fetched live from OpenAlex

We extend Bednar’s theory of a robust federation to examine the factors and institutions influencing the effectiveness of transboundary water governance in an international river basin. We examine the evolution and performance of drought adaptation in the Rio Grande/Bravo river basin of the United States and Mexico—two federal countries. Droughts and water shortages since 1990 have triggered opportunistic behavior by resource users and their governments. Analysis of case studies in three nested geographic contexts (internationally, interstate United States and interstate Mexico) generates evidence of opportunistic behavior and either limited or disputed compliance both internationally and within each country. Structural safeguards have stipulated powers and functions for water allocation and conflict resolution in all three settings, but roles and responsibilities are not clear during droughts. The limitations of structural, popular, and judicial safeguards have elevated the importance of joint monitoring, which we identify as a vital new form of safeguard.

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 score0.630
Threshold uncertainty score0.241

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.017
GPT teacher head0.205
Teacher spread0.188 · 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