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Record W4411840506 · doi:10.1080/17508487.2025.2521532

Taking time and planting seeds: learning, relationships and equity work in academic development

2025· article· en· W4411840506 on OpenAlexaboutno aff
Marie A. Vander Kloet

Bibliographic record

VenueCritical Studies in Education · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicEvaluation of Teaching Practices
Canadian institutionsnot available
FundersUniversitetet i Bergen
KeywordsEquity (law)SociologyWork (physics)SowingPedagogySocial sciencePolitical scienceAgronomyBiologyEngineering

Abstract

fetched live from OpenAlex

Canadian higher education is shaped by colonialism and can be characterized as inequitable and inaccessible. This paper considers the work of academic developers in Canadian higher education who contribute to equity work, including work on Indigenisation and Reconciliation, in their institutions. By examining how academic developers have learnt to do equity work, this paper explores tensions between conventional academic development practices and approaches necessary for bringing about social change. Participants emphasize the limitations of learning to do equity work through conventional academic methods and highlight the significance of relationships for their learning. While participants emphasize that learning to do equity work relies on and is informed by relationships; contrastingly, academic development may frame relationships as means by which conventional academic can be achieved. These tensions renew and expand questions and critiques of what knowledge informs academic development practice and what kind of changes academic development can contribute to higher education.

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)0.015
metaresearch head score (Gemma)0.022
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 score0.490
Threshold uncertainty score0.973

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.022
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0270.064
Scholarly communication0.0160.006
Open science0.0030.013
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 head0.359
GPT teacher head0.576
Teacher spread0.216 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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