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Record W4410497154 · doi:10.15173/ijsap.v9i1.5904

From “faculty-student” to “student-student” partnerships

2025· article· en· W4410497154 on OpenAlexvenueno aff

Bibliographic record

VenueInternational Journal for Students as Partners · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Practises and Engagement
Canadian institutionsnot available
Fundersnot available
KeywordsStudent engagementMathematics educationStudent teacherStudent affairsPedagogyMedical educationPsychologyPolitical scienceHigher educationMedicineTeacher education

Abstract

fetched live from OpenAlex

This research moves beyond the conventional students-as-partners discourse to explore student-student partnership practices in higher education, addressing research gaps regarding such partnerships in inter-institutional and non-Western contexts. Through a qualitative study of a student-initiated virtual service-learning project which involved student partners from two research-intensive universities in Hong Kong and Singapore, the research unveils novel conceptualizations of student partners as professional co-explorers and challenges prevailing negative perceptions of learners in Asian higher education institutions, a population that the literature has tended to characterize through stereotypical views of Confucianism. The findings emphasize possibilities for student-student partnerships to enhance agency and promote positive ripple effects in subsequent student-student and faculty-student partnerships. These benefits emerge through co-development in the perceived safer and egalitarian partnership learning community fostered between students. The study calls for restructuring partnership language formalizing integration of student-student partnerships into institutional practices. This research sets the stage for future studies on student-student partnerships in diverse contexts.

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)0.014
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.075

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.022
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0120.023
Scholarly communication0.0150.011
Open science0.0020.027
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0060.001

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 head0.147
GPT teacher head0.623
Teacher spread0.476 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations1
Published2025
Admission routes1
Has abstractyes

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