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Record W2764342470 · doi:10.15173/ijsap.v1i2.3197

Partnership in Practice: Implementing Healey’s Conceptual Model

2017· article· en· W2764342470 on OpenAlexaffvenue
Arshad Ahmad, Aadil Ali, John VanMaaren, Janette Barrington, Olivia A. Merritt, Kyle Ansilio

Bibliographic record

VenueInternational Journal for Students as Partners · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Practises and Engagement
Canadian institutionsMcMaster University
Fundersnot available
KeywordsGeneral partnershipScholarshipSustainabilityIdentity (music)SociologyScale (ratio)PedagogyMedical educationPolitical scienceMedicineArt

Abstract

fetched live from OpenAlex

This case study discusses the implementation of Healey, Flint, and Harrington's (2014) model of student engagement through partnership with staff. Healey et al. (2014) identify issues associated with “putting partnership into practice” including inclusivity and scale, power relations, reward and recognition, transition and sustainability, and identity. Faculty, staff, and students participating in a Students as Partners (SaP) Program at McMaster University’s MacPherson Institute encountered these issues during a Scholarship of Teaching and Learning (SOTL) project. This paper explores our reflections and suggests refinements related to the above five issues. It concludes by identifying possible new directions for SaP programs.

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)0.023
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.977
Threshold uncertainty score0.120

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0230.018
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0120.041
Scholarly communication0.0160.021
Open science0.0050.019
Research integrity0.0080.007
Insufficient payload (model declined to judge)0.0070.001

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 head0.220
GPT teacher head0.651
Teacher spread0.431 · 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.

Study designQualitative
DomainMethods
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

Citations17
Published2017
Admission routes2
Has abstractyes

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