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Record W2469547868 · doi:10.1080/03075079.2016.1203891

A qualitative exploration of motivations and challenges for implementing US accreditation in three Canadian universities

2016· article· en· W2469547868 on OpenAlexaboutno aff
Gerardo L. Blanco, Diep H. Luu

Bibliographic record

VenueStudies in Higher Education · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Governance and Development
Canadian institutionsnot available
FundersUniversity of Massachusetts Boston
KeywordsAccreditationHigher educationInternationalizationPublic relationsPolitical sciencePosition (finance)Qualitative researchMedical educationBusinessSociologyMedicineSocial science

Abstract

fetched live from OpenAlex

The adoption of US accreditation by non-US universities is one of the most salient manifestations of the internationalization of quality assurance in higher education. This process has been conceptualized as an exercise of global position taking by which institutions with limited financial and symbolic resources become associated with more prestigious institutions across national borders by sharing a common accreditation. However, the adoption of US accreditation has yet to be studied among institutions in well-positioned higher education systems. This study explored perceptions and experiences associated with the adoption of US institutional accreditation in three Canadian universities. The study reveals that several features of US higher education reflected in the accreditation standards, for example, general education, pose challenges for Canadian universities seeking US recognition. In addition, increased workload, resulting from the accreditation demands, became a source of disagreement between academics and administrators. This study provides grounded insights about the implementation of US accreditation beyond its geographic boundaries.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.444
Threshold uncertainty score0.978

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.293
GPT teacher head0.462
Teacher spread0.169 · 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 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

Citations16
Published2016
Admission routes1
Has abstractyes

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