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Record W1964980912 · doi:10.1080/08865655.2001.9695574

Approaches to building cooperative linkages in human resources development in the San Diego‐Tijuana and Vancouver‐Seattle binational corridor regions

2001· article· en· W1964980912 on OpenAlexvenueaboutno aff
Lawrence D. Taylor

Bibliographic record

VenueJournal of Borderlands Studies · 2001
Typearticle
Languageen
FieldSocial Sciences
TopicCross-Border Cooperation and Integration
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Regional scienceWork (physics)Position (finance)Human resourcesPolitical scienceGeographyEconomic geographyArchaeologyBusinessEngineeringLaw

Abstract

fetched live from OpenAlex

The article examines from a comparative point of view approaches to building transborder linkages in human resources development in two distinct border corridor regions of North America: San Diego‐Tijuana and Vancouver‐Seattle. The article describes the various types of educational and work‐training ties which have been established in each of the corridor regions, the organizations involved, as well as their position within the overall context of transborder relations in each zone. The article also considers how the two different regional settings have had a bearing on the development of these linkages and of the results in each case.

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)0.005
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.836
Threshold uncertainty score0.325

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0100.009
Scholarly communication0.0080.003
Open science0.0020.008
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 head0.125
GPT teacher head0.378
Teacher spread0.253 · 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 designQualitative
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

Citations1
Published2001
Admission routes2
Has abstractyes

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