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Integrating Cultural Perspectives into International Interdisciplinary Work

2021· article· en· W3168161350 on OpenAlex
Karen I. Trebitz, SCOTT J. FENNEMA, Keegan A. Hicks

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Contemporary Water Research & Education · 2021
Typearticle
Languageen
FieldDecision Sciences
TopicInterdisciplinary Research and Collaboration
Canadian institutionsUniversity of Waterloo
FundersNational Science Foundation
KeywordsDisciplineResource (disambiguation)Natural resource managementBridge (graph theory)Natural resourceWork (physics)Cultural diversityNatural (archaeology)SociologyGraduate studentsPedagogyEngineering ethicsPolitical scienceSocial scienceGeographyEngineeringMedicineAnthropologyArchaeology

Abstract

fetched live from OpenAlex

Abstract There are well‐established methods for working in interdisciplinary natural resource management settings, but place‐based cultural differences are often poorly integrated into interdisciplinary projects. Intercultural adequacy is necessary to ensure that water management strategies are acceptable within the local contexts of water users. In this study we followed four cohorts of graduate students from Canada, Chile, Cuba, and the United States that participated in an international graduate‐level water resource management course hosted at the Universidad de Concepción in Chile. The North American students participated in post‐experience surveys and interviews to assess changes in their interdisciplinary and intercultural comfort levels. The interviews and survey identified factors that enhanced or detracted from their progress towards integrating disciplinary and cultural differences into their work. Though course material promoted interdisciplinary collaborations across various disciplinary cultures, participants noted that traditional methods of integrating did not adequately bridge differences in place‐based cultural worldviews. We propose a framework developed during the experience to integrate place‐based cultural differences into all phases of the interdisciplinary research and natural resource management processes.

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)0.010
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.502
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0020.004
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.175
GPT teacher head0.527
Teacher spread0.352 · 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