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Record W2956612474 · doi:10.1080/07294360.2019.1638349

Motivations, barriers, & understandings: how students at four universities perceive student–faculty partnership programs

2019· article· en· W2956612474 on OpenAlexafffund
Elizabeth Marquis, Ajitha Jayaratnam, Tianqi Lei, Anamika Mishra

Bibliographic record

VenueHigher Education Research & Development · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Practises and Engagement
Canadian institutionsMcMaster University
FundersMcMaster University
KeywordsGeneral partnershipPerceptionHigher educationPublic relationsOrder (exchange)Survey data collectionPolitical sciencePedagogyMedical educationPsychologyMedicineBusiness

Abstract

fetched live from OpenAlex

Extracurricular student–staff partnership activities are increasingly common in higher education institutions, but concerns have been expressed about their relative inclusivity. In order to contribute to understanding of why students do and do not take part in such initiatives, this study draws on data from a survey of students at four institutions, in three different countries, with established extracurricular partnership programs. Though the findings indicate some preliminary differences between participants at the four institutions, they also demonstrate a number of shared perceptions, including similar understandings of key features of partnership and shared perceptions of barriers to participation. Implications for partnership practice and research are discussed.

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)0.009
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.010
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0050.004
Scholarly communication0.0070.003
Open science0.0010.008
Research integrity0.0020.003
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 head0.203
GPT teacher head0.467
Teacher spread0.265 · 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 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

Citations20
Published2019
Admission routes2
Has abstractyes

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