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Internationalizing Canadian Higher Education through North-South Partnerships: A Critical Case Study of Policy Enactment and Programming Practices in Tanzania

2013· article· en· W29028324 on OpenAlexfundaboutno aff
Allyson Larkin

Bibliographic record

VenueInorganic Chemistry · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Governance and Development
Canadian institutionsnot available
FundersDivision of ChemistryNational Institute of General Medical SciencesBiological and Environmental ResearchKing's University College
KeywordsTanzaniaPolitical scienceEconomic growthPublic administrationGeographyEnvironmental planningEconomics

Abstract

fetched live from OpenAlex

The contemporary internationalization of higher education promotes the formation of North-South (N-S) partnerships to facilitate access to new research sites and opportunities for international programming. This study conceptualizes N-S partnerships as an extension of internationalization policy. In the current context of internationalization, there is a reliance on higher education to produce economic benefits to support national economic objectives. There are particular concerns, however, with a practice of N-S partnerships that are enacted in communities located in the Global South. Internationalization policy does not adhere to the principles of N-S partnership outlined in multilateral agreements and is increasingly focused on the production of economic returns from investment in partnerships projects. This research focuses on the enactment of a specific N-S ISL partnership in Tanzania to consider the effects of higher education internationalization on local communities. It raises critical concerns for a socially just practice of international partnership.

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 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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.422
Threshold uncertainty score0.741

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.062
GPT teacher head0.382
Teacher spread0.320 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations8
Published2013
Admission routes2
Has abstractyes

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