Teachers of Chinese Ancestry: interaction of identities and professional roles
Bibliographic record
Abstract
The research presented in this paper, based on ethnographic interviews with 19 female and 6 male Canadian teachers of Chinese ancestry, is part of a larger study examining perceptions of careers in teaching by secondary school and university students as well as practising teachers, all of minority Chinese or Punjabi Sikh ancestry (Beynon, Toohey & Kishor, 1992; Beynon & Toohey, 1995; Beynon & Toohey, 1998; Hirji & Beynon, 2000). Drawing on Britzman's (1992) theoretical distinction between teachers' roles and identities, the thesis of our research is that "role", which Britzman describes as impermeable and prescribed by normative institutional practices and ideologies, is, rather, potentially porous. We see that teachers of minority ancestry infuse their roles with new dimensions that draw on their identities. Hall's (1996) materialist theorizing helps us to see how identity, multifaceted and fluid, can be a source for negotiating roles. We recommend changes in teacher education and schools that would help to authorize transformation so that these settings which presently privilege the values, practices and discourses of the dominant Anglo-European Canadian society can become more inclusive of the identities and experiences of minority teachers.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.016 | 0.009 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".