Beyond tokenism in the field? On the learning of a Mathematics teacher educator and faculty supervisor
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
Supervision of student teachers in their field experience is one of the practices that characterizes the work of many teacher educators. This paper takes up the issue of mathematics teacher education field experience, drawing on the conceptual tools of Bourdieu’s social field theory to interpret data from a self-study on the role of supervision “in the field.” The data storylines presented in this paper convey one mathematics teacher educator’s efforts to disrupt and reconceptualize the network of relations in teacher education field experience, with a goal of understanding how one’s professional practice as a supervisor might shape and influence a more dynamic view of these networks. The paper argues for taking a reflexive stance in teacher education, to reveal the habits and cultural capital shaping action in/of the field, and to support teacher educators as they trouble the discursive network of relations—represented in this paper through five storylines—of mathematics teacher education field experience and associated supervision.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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