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Record W4280495301 · doi:10.15173/ijsap.v6i1.4837

Student partnership to achieve cultural change

2022· article· en· W4280495301 on OpenAlexvenueno aff
Shuab Gamote, Leonie Edmead, Bethany Stewart, Tamara Patrick, Claire Hamshire, Rachel Forsyth

Bibliographic record

VenueInternational Journal for Students as Partners · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Practises and Engagement
Canadian institutionsnot available
Fundersnot available
KeywordsGeneral partnershipEthnic groupPublic relationsPolitical scienceSet (abstract data type)White paperPedagogySociologyComputer science

Abstract

fetched live from OpenAlex

This case study offers reflections on a student-led collaboration between the university and its student representative body (the Students’ Union) and outlines the successes and challenges of partnership to address institutional cultural change. The project was set up to improve students’ experiences and raise awareness of the existence of differential outcomes between Black, Asian, or minority ethnic (BAME) and white students and to promote strategies to build meaningful relationships through the development of internal and external networks. It was led by 11 BAME student ambassadors who developed and delivered campaigns and events for students and who linked with university staff and the Students’ Union to represent students’ views on ways to achieve positive change on campus. Partnership working was essential to enable the student ambassadors to develop trust, make their own changes, and influence key decision makers across the University.

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)0.017
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.020
Threshold uncertainty score0.090

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.018
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0200.010
Scholarly communication0.0190.009
Open science0.0030.037
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0110.003

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 head0.219
GPT teacher head0.621
Teacher spread0.401 · 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 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

Citations5
Published2022
Admission routes1
Has abstractyes

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