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Record W2739411081 · doi:10.3390/resources6030032

Modeling Cross-Border Regions, Place-Making, and Resource Management: A Delphi Analysis

2017· article· en· W2739411081 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.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueResources · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicCross-Border Cooperation and Integration
Canadian institutionsUniversity of the Fraser Valley
FundersGovernment of CanadaWestern Washington University
KeywordsDelphi methodConvergence (economics)DelphiResource (disambiguation)Value (mathematics)Spillover effectLogitRegional scienceProcess (computing)Economic geographyComputer scienceOperations researchEconomicsGeographyEconometricsMicroeconomicsEngineeringEconomic growthArtificial intelligence

Abstract

fetched live from OpenAlex

Along international borders, spillover of resource management issues is a growing challenge. Development of cross-border regions (CBRs) is seen as an emerging means of addressing these issues. A set of theoretical models, geo-economic mobilization and a resource-focused territorial program of place-making have been proposed as a lens for understanding why such change could occur. From this theory, we identify three C’s as critical initial or necessary conditions to start the process: common territorial identity, convergence of knowledge and values, willingness for cooperation. We then utilize results of a Delphi study in the Fraser Lowland, a sub-district of the American-Canadian Cascadia borderland, to test if these three are present and actively working together. Our analysis based on both cumulative logit and mixed-effect modeling confirms the active existence of the three C’s demonstrating the value of these theoretical models. However, the Delphi also shows that not all in this region are convinced of cross-border convergence and case studies provide mixed signals of successful cross-border resource management, indicating that sufficient conditions are yet to be fully met. Thus, our results confirm the value of these models as a lens to view events, but leave many questions to be researched.

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 categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.863
Threshold uncertainty score0.999

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 studies0.0040.000
Scholarly communication0.0020.000
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 head0.028
GPT teacher head0.435
Teacher spread0.406 · 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