Bibliographic record
Abstract
This research highlights the synchronous and asynchronous learning journey of a PhD student and supervisor as they entered the relational work of narrative inquiry in music teacher education during the COVID-19 global pandemic. Despite the challenges of unplanned distance learning, the online location became a pivotal space of guidance about teaching and learning. This collaborative research came about through an invitation from a doctoral supervisor to a PhD student (in the spring of 2020) to observe teaching an 18-hour, face-to-face, general music education course (Grades 4–10) for teacher candidates at a southwestern Ontario university. As the face-to-face course quickly shifted to the online location during COVID-19, so did the place of interaction. The landscape became defined and confined to the glow of computer screens, rising and setting through Microsoft Teams. This research draws on shared dialogue as a guide to exploring the three-dimensional framework of narrative inquiry’s commonplaces – temporality, sociality, and place (Connelly & Clandinin, 2006). The synchronous nature of this collaborative research allows experience, analysis, and synthesis to become a place of understanding. Findings revealed three thematic threads: online location, mentorship, and vulnerability as a pedagogical process. Music educators are encouraged to find new ways of conceptualising teaching and learning by considering the online location as a place or a medium that affords unique possibilities for collaboration. What began as a possible limitation of not being able to experience teaching and learning face-to-face becomes a rich space for inquiring into learning through the three-dimensional framework of narrative inquiry.
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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.013 | 0.015 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.102 | 0.044 |
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".