making of a professional identity
Bibliographic record
Abstract
This paper illustrates how metaphor can provide a vital link between the private and often idiosyn-cratic world of ‘felt-reality ’ and the propositional world of theories and constructs in which most academic and professional discourses are conducted. Drawing on Schön’s concept of reflection as ‘seeing-as ’ and Heron’s model of ‘ways of knowing’, it suggests that the exploration and articulation of an individual’s use of metaphor is an important element in the process of demystifying the passage of ‘intuitive ’ knowledge into professional practice. The author demonstrates how part of her profes-sional identity has been constructed through reflective writing but questions whether work of this kind has any place in the current outcomes-driven climate of research assessment in academia. Talking turtle … our argument is not simply that the artistic imagination could play a larger role in professional learning, but that it should do so. (Winter et al., 1999, p. 2; original emphasis) On top of my computer is a tiny hand-carved piece of jade in the shape of a turtle, bought in a First Nations craft shop in Vancouver. It is a tangible reminder of an enjoyable adult education conference I attended in 2000. It also speaks to me of the importance of myths and imagery in professional learning and related research—and
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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 | 0.028 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.028 | 0.039 |
| Scholarly communication | 0.020 | 0.017 |
| Open science | 0.002 | 0.023 |
| Research integrity | 0.007 | 0.010 |
| Insufficient payload (model declined to judge) | 0.012 | 0.005 |
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".