Letting the Light In: A Collaborative Self-Study of Practicum Mentoring
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
This article documents a year-long collaborative self-study of three teacher educators engaged in a practicum innovation in a teacher education program. This study, which is part of a larger study examining practicum-based seminars called Particulars of Practice (POP), focuses on exploring our own practices and identities within this innovation. Given this new structure in the program, we had many questions about how we each engaged with mentoring within this innovation, and what conceptions and assumptions were being surfaced for us about our roles, identities, and practices in practicum mentoring. The data included an email thread, personal reflections, and collaborative meeting transcripts that represented our experiences with the POP innovation. Using braiding as a methodological approach to honour all three sets of data, we were able to generate results that fell into two categories: reflections on the nature of self study and the knowledge gained about our identities, practices and roles from this research. We assert that the nature of self study involves vulnerability, difficult conversations, and multiplicity of perspectives. The knowledge gained from our collaborative self-study is identified as challenging preconceptions, seeing teacher candidates in new ways, and learning as a mirroring process.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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