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Record W3138784911 · doi:10.1080/24711616.2020.1823913

Moving toward the Internationalization of an Academic Society: Twenty-First Century Perspectives and Collaborations

2021· article· en· W3138784911 on OpenAlexaboutno aff
Betty A. Block, Tara Tietjen-Smith

Bibliographic record

VenueInternational Journal of Kinesiology in Higher Education · 2021
Typearticle
Languageen
FieldHealth Professions
TopicPhysical Education and Pedagogy
Canadian institutionsnot available
Fundersnot available
KeywordsInternationalizationKinesiologyOpenness to experienceContext (archaeology)Higher educationPolitical scienceDiversity (politics)Internationalization of Higher EducationSociologySocial sciencePublic relationsLibrary scienceManagementMedicineMedical educationPsychologyLawHistory

Abstract

fetched live from OpenAlex

International perspectives and collaborations are critical to the health of the kinesiology discipline during this supercomplex age. To that end, the National Association for Kinesiology in Higher Education (NAKHE) has adopted internationalization goals that support international faculty, joining forces with other academic societies across the world to promote innovation in programming, and to create international scholar leaders. Ideas related to specific internationalization virtues within kinesiology that were developed with international colleagues in Montreal, Canada at the PHE Canada Research Council Forum (May 2019) and at the Association Internationale des Écoles Supérieures d’Éducation Physique (AISEP, International Association for Physical Education in Higher Education) Conference at Adelphi University, Garden City, New York (June 2019) will be discussed. Themes coalesced into specific virtues including Collaboration, Valuing Diversity, Openness to Interdisciplinarity, Innovation, and Leadership. These themes will be discussed and put into the context of NAKHE’s internationalization efforts.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.412
Threshold uncertainty score0.710

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 integrity0.0000.001
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 head0.086
GPT teacher head0.470
Teacher spread0.384 · 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

Citations3
Published2021
Admission routes1
Has abstractyes

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