Bibliographic record
Abstract
This article explores a collaborative teacher self-study in which two teacher educators/podcasters, inquired personally and collectively into the possibilities for podcasts in/as teacher education. Extending framings of podcasts to include more than content-transmission or replacement of previous texts or pedagogical practices, we further theorize the social, exploratory, and most importantly, (co)creative, within the process of making podcasts in/as teacher education. We wonder about how and why podcasting, informed by self-study practices, might support the articulation, questioning, returning to, and (re)inventing of professional identities within teacher education. This article-as-podcast enmeshes our findings and discussion as different ‘episodes’ to first share our methods, and then detail the concept of informality in podcasting and teacher education, and to explore the power of polyvocality. Finally, we end with some provocations for the reader – questions and wonderings about the ways in which the process of podcasting might prompt building relationality between a range of audiences to create space for teachers’ imaginings of themselves and what it means to teach.
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 | 0.011 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.017 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".