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Record W2947517102 · doi:10.15173/ijsap.v3i1.3727

“More than just a student”: How co-creation of the curriculum fosters third spaces in ways of working, identity, and impact

2019· article· en· W2947517102 on OpenAlexvenueno aff
Tanya Lubicz-Nawrocka

Bibliographic record

VenueInternational Journal for Students as Partners · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Practises and Engagement
Canadian institutionsnot available
Fundersnot available
KeywordsCurriculumGeneral partnershipSpace (punctuation)Reciprocity (cultural anthropology)PedagogyIdentity (music)SociologyWork (physics)Mathematics educationPsychologyPolitical scienceEngineeringSocial scienceComputer science

Abstract

fetched live from OpenAlex

The Third Space (Bhabha, 2004) represents non-traditional roles, processes, relationships, and spaces in which individuals work and have impact. This article presents qualitative research into 13 different curriculum co-creation initiatives at five Scottish universities and analyses the forms of Third Space that emerge.The findings highlight that curriculum co-creation can foster Third Spaces that include: new ways of working in learning and teaching, student development in a space between traditional student and teacher roles and identities, and impact in civic engagement within and beyond the university. The respect and reciprocity that characterise curriculum co-creation can greatly benefit students’ personal and professional development as individuals. In addition, I suggest that the Third Space of civic engagement can advance the Third Mission of universities (beyond impact in the first two missions of teaching and research) when students and teachers work in partnership to have a positive effect on the wider society.

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)0.013
metaresearch head score (Gemma)0.015
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 score0.017
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0170.022
Scholarly communication0.0140.008
Open science0.0020.014
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.106
GPT teacher head0.556
Teacher spread0.450 · 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

Citations39
Published2019
Admission routes1
Has abstractyes

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