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Record W4410496463 · doi:10.15173/ijsap.v9i1.5969

Student Partnership Impact Awards (SPIA)

2025· article· en· W4410496463 on OpenAlexvenueno aff
Gemma Mansi

Bibliographic record

VenueInternational Journal for Students as Partners · 2025
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsnot available
FundersUniversity of WestminsterUniversity of BathUniversity of RoehamptonEdge Hill University
KeywordsGeneral partnershipPolitical scienceLaw

Abstract

fetched live from OpenAlex

In 2022, the Staff Educational Development Association (SEDA) developed the Student Partnership Impact Award (SPIA), providing students and recent alumni with an opportunity to be professionally accredited for their leadership abilities through partnership. SEDA is a professional association for educational developers based in the UK. The SPIA award aims to expand SEDA’s community of educational developers by reaching out to other national and international students and staff working in partnership. SEDA’s development team, of which I am part of, carried out a review of the award procedures for quality assurance purposes. The review process found a lack of leadership narrative in unsuccessful applications. This stemmed from applicants not being ultimately responsible for a project and, as a result, these applicants subsequently seemed unable to claim any leadership, which set the tone of applicants being subordinates to the staff project lead. These findings raised for me and the development team further questions about students’ exposure to leadership skills development and students’ ability to recognise their own leadership skills as part of their employability skills development. This case study explores thematic factors affecting students’ ability to confidently articulate themselves as leaders in a student partnership setting and what we can do as staff to support students in developing those graduate attributes. It also provides reflections and ideas for colleagues considering putting students forward for professional accreditation or potentially developing their own awards scheme.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.083
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.093
GPT teacher head0.661
Teacher spread0.568 · 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 teacher head, not a consensus.

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

Citations1
Published2025
Admission routes1
Has abstractyes

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