MétaCan
Menu
Back to cohort
Record W2212260149 · doi:10.1080/11926422.2015.1035296

Subnational diplomacy in the Great Lakes region: toward explaining variation between water quality and quantity regimes

2015· article· en· W2212260149 on OpenAlexaffabout
Carolyn Johns, Adam Thorn

Bibliographic record

VenueCanadian Foreign Policy Journal · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Systems and Governance
Canadian institutionsToronto Metropolitan University
FundersAustralian Government
KeywordsDiplomacyPolitical scienceForeign policyFederalismVariation (astronomy)Quality (philosophy)Resource (disambiguation)Political economyPublic administrationEconomicsPoliticsLaw

Abstract

fetched live from OpenAlex

/RésumésSubnational diplomacy is increasingly important in foreign policy and Canada-United States relations. The Great Lakes region represents an excellent laboratory for studying the role of subnational governments in foreign policy. This article focuses on water policy in the Great Lakes region, and the central research question of why subnational diplomacy varies across water quality and water quantity policy regimes. Using a comparative case approach, the paper investigates the degree to which the character of the policy challenge itself, constitutional and institutional arrangements, and the nature of federalism and intergovernmental relations in the two countries explain differing levels of subnational diplomacy. One case illustrates how institutionalized relationships between subnational units that share interests in a transboundary resource cooperate to engage in subnational diplomacy; the other illustrates more traditional involvement of subnational governments in foreign policy, highlighting that these factors hold significant promise in explaining variation in subnational diplomacy and support existing theory in the paradiplomacy literature.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.157
Threshold uncertainty score0.312

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.152
GPT teacher head0.369
Teacher spread0.216 · 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 designObservational
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

Citations9
Published2015
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Foreign Policy JournalSame topicPolitical Systems and GovernanceFrench-language works237,207