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Record W2730584098 · doi:10.36366/frontiers.v21i1.307

A Necessary Partnership: Study Abroad and Sustainability in Higher Education

2011· article· en· W2730584098 on OpenAlexfundaboutno aff
Andrea M.W. Dvorak, Lars D. Christiansen, Nancy L. Fischer, Joseph B. Underhill

Bibliographic record

VenueFrontiers The Interdisciplinary Journal of Study Abroad · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Education and Multiculturalism
Canadian institutionsnot available
FundersGovernment of Canada
KeywordsGeneral partnershipSustainabilityInternationalizationStudy abroadPolitical sciencePoliticsHigher educationEnvironmental educationEconomic growthSociologyEngineering ethicsPublic relationsBusinessPedagogyEngineeringEcologyEconomicsInternational trade

Abstract

fetched live from OpenAlex

In this article, we will explore two case studies of programs abroad that seriously engaged both the contradictions and opportunities inherent in the idea of sustainable international education. The first examines environmental politics and ecology in New Zealand and the Cook Islands and the second compares sustainable urban practices in Canada and the United States. Based on the lessons learned from these case studies, we will argue that partnership between internationalization and sustainability efforts is necessary to help institutions of higher learning become both global and “green.” To that effect, we discuss specific and concrete ways to “green” study abroad courses throughout this paper, particularly within the two case studies and in our concluding discussion of strategies for international educators, faculty, and higher education administrators.

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)0.008
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.022
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0220.019
Scholarly communication0.0100.011
Open science0.0010.022
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0090.001

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 head0.391
Teacher spread0.349 · 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 designNot applicable
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

Citations20
Published2011
Admission routes2
Has abstractyes

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