Sustainable open textbook models for social justice
Bibliographic record
Abstract
Growing inequity continues to manifest within and between higher education institutions, highlighting the plight of the disadvantaged versus the advantaged. Against this backdrop, students’ ability to access quality textbooks and educational resources with locally relevant content presents a critical equity issue. Open textbooks provide opportunities to address social justice in the classroom. Highlighting the injustices which motivated authors in the Digital Open Textbooks for Development (DOT4D) initiative at the University of Cape Town (UCT), this study uses Catherine Bovill’s framework of inclusion to examine the processes of 11 open textbook initiatives at UCT in terms of their degrees of inclusivity, with a focus on student participation. The authors draw on the work of political philosopher Nancy Fraser and her central norm of “parity of participation” in order to analyze the cases in terms of their ability to provide affirmative or transformative remedies to injustice. The data presented in this study were derived from a mixed-methods research and implementation approach, in which a survey was administered to the lead authors of the 11 open textbook initiatives. The proposals submitted by ten of these initiatives in their application for a DOT4D grant and their grant reports were also an important data source. These data, combined with insights from two rounds of in-depth interviews with five authors from the study sample provides insight into the injustices academics were grappling with and the ways in which they endeavored to address them. This article articulates four open textbook models with varying degrees of colleague and student inclusion. Examining authorship, quality assurance and publishing activities as nodes of inclusivity, the article provides insight into the strategies open textbook authors at UCT adopt in order to address social injustice in the classroom related to access and representation. It also considers ways in which higher education institutions can address sustainability in order to support the endeavor.
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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 | 0.009 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.007 | 0.029 |
| Scholarly communication | 0.016 | 0.017 |
| Open science | 0.004 | 0.019 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.025 | 0.003 |
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".