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Record W2125171906 · doi:10.5206/cie-eci.v42i2.9231

The Issue of Mutuality in Canada-China Educational Collaboration

2013· article· en· W2125171906 on OpenAlexaffvenueabout
Phirom Leng, Julia Pan

Bibliographic record

VenueComparative and International Education · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Governance and Development
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSolidarityChinaConsolidation (business)AutonomySociologyEquity (law)Linkage (software)Political scienceContext (archaeology)Public relationsLawGeography

Abstract

fetched live from OpenAlex

This paper examines the power relationships in two major Canada-China university linkage programs which ran between 1989 and 2001: the Canada-China University Linkage Program [CCULP] (1989-1995) and the Special University Linkage Consolidation Program [SULCP] (1996-2001). The study adopts the cosmopolitan concept of mutuality as a theoretical lens and employs the analytical method of constant comparison of qualitative data to explore the context surrounding the mutuality evidenced in CCULP/SULCP. The findings show that both programs manifested the four characteristics of mutuality identified by Johan Galtung: equity, autonomy, solidarity and participation. Human values or cultural agency were identified as the key factor making mutuality possible, as well as nurturing and sustaining the relationships between Canadian and Chinese participants. This study suggests that cosmopolitanism be given more attention in this increasingly interconnected world. Its primary emphasis is on human relationships, and this dimension needs to be given more space in international academic relations.

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)0.011
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.965
Threshold uncertainty score0.749

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0150.009
Scholarly communication0.0050.002
Open science0.0010.008
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.029
GPT teacher head0.385
Teacher spread0.357 · 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

Citations14
Published2013
Admission routes3
Has abstractyes

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