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Record W3215490778 · doi:10.1080/14662043.2021.1997192

Patterns in nascent, ascendant and mature border security: regional comparisons in transgovernmental coordination, cooperation, and collaboration

2021· article· en· W3215490778 on OpenAlexafffund
Christian Leuprecht, Emmanuel Brunet‐Jailly, Todd Hataley, Tim Legrand

Bibliographic record

VenueCommonwealth and Comparative Politics · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicCross-Border Cooperation and Integration
Canadian institutionsUniversity of VictoriaFleming CollegeRoyal Military College of CanadaQueen's University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsEnforcementKey (lock)Political scienceSimilarity (geometry)Public relationsBusinessEcologyLawBiologyComputer science

Abstract

fetched live from OpenAlex

This special issue raises the prospect of trust-based determinants of security communities other than cultural similarity. The case studies in this special issue document the emergence of cross-border and transgovernmental policy and enforcement networks that facilitate policy development, implementation and alignment through coordination, cooperation, and collaboration: nascent communities coordinate, ascendant communities coordinate and cooperate but struggle to collaborate, while mature communities coordinate, cooperate, and collaborate. Specifically, pluralistic forms of communication and interactions away from the actual borderline seem to play a key role in the emergence of friendly and trustful relationships among border dyads that need not necessarily be contiguous.

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)0.003
metaresearch head score (Gemma)0.013
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 score0.008
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.006
Science and technology studies0.0020.004
Scholarly communication0.0050.004
Open science0.0010.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.042
GPT teacher head0.392
Teacher spread0.350 · 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

Citations7
Published2021
Admission routes2
Has abstractyes

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