Taking time and planting seeds: learning, relationships and equity work in academic development
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.027 | 0.064 |
| Scholarly communication | 0.016 | 0.006 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".