One Classroom at a Time: How Better Teaching Can Make College More Equitable
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
David Gooblar’s “One Classroom at a Time” is a practice-centred book on the pressing discussion on equity, diversity, and inclusion in higher education. The book opens with a powerful statement: “the majority of our existing curricula are designed for imaginary students” (Gooblar, 2025, p. 17). This notion of the “imaginary student,” described as ones who populate elite institutions and dominate the discussion on curriculum design and pedagogy, is deeply anchored throughout the book. In response to the long-standing archetype of fragmentation, competition, gatekeeping, and favouritism that dominate curricula and pedagogy, this thought-provoking book draws on evidence from psychological studies and historical analysis to challenge the practices of disembeddedness. The increasingly diverse student population in higher education underscores the need for educators, staff, and administrators to shift from a deep-rooted archetype to an identity-conscious pedagogy. With a writing style that is vivid, critical, accessible, and well informed by research and classroom experience, the author creates a book suitable for all audiences, providing actionable classroom suggestions, toolkits, and future recommendations. Amid today’s complex political climate, this book is an unapologetic defence of advocacy efforts for a more equitable 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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it