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Record W2613086703 · doi:10.15173/ijsap.v1i1.3079

Students as Partners in the Real World – A Whole-Institution Approach

2017· article· en· W2613086703 on OpenAlexvenueno aff
Natasha Shaw, Caroline Rueckert, Judith Smith, Jennifer Tredinnick, Maddison Lee

Bibliographic record

VenueInternational Journal for Students as Partners · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Practises and Engagement
Canadian institutionsnot available
Fundersnot available
KeywordsGeneral partnershipInstitutionPublic relationsProcess (computing)Knowledge managementRelation (database)Value (mathematics)SociologyBusinessPolitical scienceComputer scienceSocial science

Abstract

fetched live from OpenAlex

Students as Partners (SaP) is an approach to student engagement that has gained much traction in recent years. Evidence shows that it adds value to the learning experience and provides opportunities for students to develop the capabilities needed in their future pathways. This paper documents one university’s approach to embedding partnerships in its institutional culture. The paper begins by contextualising the process in relation to wider institutional goals and outlines the three phases of implementation. This case study argues that to enable a whole-institution approach to SaP, it has been necessary to invest in strategies at a number of levels that enable partnership, from high-end policy and protocols to providing opportunities for staff and students to shape their own partnerships.

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)0.016
metaresearch head score (Gemma)0.013
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.084

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0110.016
Scholarly communication0.0240.018
Open science0.0030.034
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0120.002

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 head0.143
GPT teacher head0.608
Teacher spread0.465 · 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
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

Citations13
Published2017
Admission routes1
Has abstractyes

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