Bibliographic record
Abstract
As representatives of a discipline and gatekeepers to disciplinary communities, faculty have a powerful role in defining what disciplines are and who has access. In exposing students to disciplinary conventions, instructors may present disciplinary norms as inflexible, which may limit access or make disciplines feel unwelcoming. Students may be faced with reconciling their culture’s ways of knowing with disciplinary ways of knowing, and instructors may face conflicts between preparing students for disciplinary expectations and providing an equitable classroom open to non-dominant ways of knowing and communicating. This multiple case study investigates how faculty think about disciplinary norms and equitable pedagogies, whether tensions arise in their disciplinary teaching, and how they manage those tensions. Findings indicate that tensions created opportunities for reflection and led to changes in teaching indicative of double-loop learning. Departmental tensions suggest a paradigm shift in Earth Science teaching pedagogy, and institutional tensions suggest that the university is undergoing organizational learning. This study also indicates that tensions occurred at multiple levels (individual, departmental, discipline, and institution/university) which has implications for challenges in making learning environments more equitable. Existing and potential approaches for addressing these challenges are discussed.
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 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 | 0.069 | 0.105 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.010 |
| Scholarly communication | 0.015 | 0.010 |
| Open science | 0.003 | 0.018 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".