Commitments to a Community of Artistic Inquiry
Bibliographic record
Abstract
The purpose of this inquiry is to investigate how a/r/tography is uniquely situated to enact, develop, and problematize 'becoming pedagogical' in an arts-based cohort in a teacher education program. This particular study purposefully grapples with visual and performing arts, in an elementary teacher education program, as teacher candidates 'learn to learn' how to inquire through their disciplinary and interdisciplinary frames of mind. We take the position that arts-based research adds to the diversity and complexity inherent in understandings about education and pedagogy. This research was infused through principles of teaching, music and movement, and visual arts education classes at The University of British Columbia. To learn about adopting an a/r/tographic stance in their journeys of becoming teachers, teacher candidates were actively involved in arts-based research workshops, the development of an art exhibition, learning to infuse creative pedagogies across the curriculum, and sharing their arts-based research projects. Their art took the form of public performances with artistic (music, dance, drama, visual) representations of curriculum.
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 | 0.052 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.039 | 0.115 |
| Scholarly communication | 0.038 | 0.019 |
| Open science | 0.006 | 0.034 |
| Research integrity | 0.006 | 0.012 |
| Insufficient payload (model declined to judge) | 0.008 | 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".