Teachers who teach their practice: the modulation of hybridised professional teacher identities in work-related educational programmes in Canada
Bibliographic record
Abstract
This article explores diversity in the identity of vocational teachers and the ways these identities are both situated in cultural and political contexts and built upon life and career histories. The analysis is developed from a study of work-related programmes offered to students aged 15-18 in one school board in Canada, with a particular focus on five courses. Teacher identity emerged as a significant factor that supported the distinctly vocational-educational learner experience that was identified through the research. The case-study approach enabled us to examine features of the context in relation to teacher identity. In particular, we propose that vocational teacher identities were modulated in relation to accountabilities to different ‘communities of practice’, such as those of prior or concurrent industry affiliations. We identify features of the policy context that enabled this modulation of identity and the formation of a ‘community of practice’ among technology teachers. Rich qualitative data is re-presented in conceptual terms which may be useful in framing and guiding educational decisions that are attuned to developing authentic vocational and educational experiences for young people. This analysis of vocational teacher identities not only expands upon current perspectives on teacher identity, but also throws new light on theoretical and practical debates surrounding teacher agency and curriculum control within heavily mandated and monitored professional contexts such as schools.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.021 | 0.011 |
| Scholarly communication | 0.007 | 0.001 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".