Theater as Representation (TAR) in the Teaching of Teacher and Administrator Preparation Programs.
Bibliographic record
Abstract
ABSTRACT: Theater as representation (TAR) has been used in pre-service and in-service teacher and administrator preparation programs since 1998. This paper places TAR within a pedagogical arena that further solidifies its place as an instrument for leadership professional development in B.Ed., M.Ed., and in-service programs. Maxine Greene (1995) challenges us to seek the use of imagination within our pre-service teacher preparation programs. … It is difficult for me to teach educational history or philosophy to teachers-to-be without engaging them in the domain of imagination and metaphor. How else are they to make meaning out of the discrepant things they learn? How else are they to see themselves as practitioners, working to choose, working to teach in an often indecipherable world? (p. 99) The use of imagination and metaphor are foundational infrastructure girders in teaching pedagogy. But more often than not, our pre and in service teachers and administrators have seen their imagination and understanding of metaphor in creative adventures somewhat stifled (if not put into stasis) with their secondary school and undergraduate educational experiences. The field of educational administrator preparation is going in different directions in a number of provincial and state jurisdictions. Clearly with many politically and fiscally conservative minded governments coming to power, much of the current legislation has skewed the field to what seems to be a more right-wing, rules-based approach to school governance. For many Masters students, the degree itself is more of a means towards a financial scale upgrade or job requirement more than for true professional development. For pre-service teachers, a surface knowledge of such administrative tasks as classroom management, negligence liability, reporting responsibilities and due process in student academic and behavioral assessment(s) have become virtually obligatory. There are a variety of teaching mediums employed in both pre-service (teacher preparation) 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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.019 | 0.003 |
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".