Transforming Self and Practice: Collecting Evidence in a Hall of Concave Mirrors
Bibliographic record
Abstract
Abstract In this chapter, we develop the “hall of mirrors” metaphor for practicum learning, introduced in Schön (1987) and expanded upon in MacKinnon (1989), as a heuristic for considering the ways in which we might claim that our practice has transformed through engaging with self-study methodology. First, we reconsider Schön's (1987) ideas about professional learning and their implications for our understanding of self-study, specifically, his claim that professional learning is unique in that a hall of mirrors is created “on the basis of parallelisms between practice and practicum” (p. 297). This parallelism is particularly relevant for teacher educators as we often aim to engage our students in the very practices we hope they will enact in schools. In so doing, we consider MacKinnon's cautions about over-simplifying any model of teacher education. Second, we use these ideas to each select excerpts from self-study work we have conducted in our careers to identify moments of transformed thinking about teacher education. Finally, we arrived at a new metaphor of a concave mirror for a retrospective look at the results of our self-study investigations. A concave mirror, unlike its planar counterpart, creates different orientations of images (right-side up vs. up-side down), depending on how far an object is away. We develop this final metaphor as a way of thinking about the differences inherent in treating self-study work at a distance, after some time has passed from the original moments when we were embedded in a hall-of-mirrors relationship with our students.
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 | 0.035 | 0.090 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.005 | 0.011 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".