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Teachers of Punjabi Sikh Ancestry: Their Perceptions of Their Roles in the British Columbia Education System

2000· article· en· W50805614 on OpenAlexfundvenueaboutno aff
Shemina Hirji, June Beynon

Bibliographic record

VenueAlberta Journal of Educational Research · 2000
Typearticle
Languageen
FieldArts and Humanities
TopicSouth Asian Studies and Diaspora
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPerceptionPsychologySociologyGender studiesMathematics education

Abstract

fetched live from OpenAlex

This study examines the perceptions of teachers of Punjabi Sikh ancestry of their roles in the British Columbia public education system. Twenty teachers, 13 females and seven males, were interviewed. Three of the participants were born in Canada, 17 had immigrated to Canada. The participants ranged in age from their early 20s to their late 40s. The results of this investigation indicate that these teachers see themselves playing a wide range of roles in the education system. They recount that they serve as bridges between the Punjabi Sikh community and the education system, acting as translators, cultural informants, and role models. These teachers are also committed to influencing selected cultural values of Punjabi Sikh parents in order to reflect mainstream attitudes toward education and gender roles. This research has important implications for teacher education programs and public school districts that recruit, train, and employ minority teachers. This research suggests that it is critical to acknowledge teachers of Punjabi Sikh ancestry not just as "professional ethnics," but as educators with a range of skills and talents as varied as those of their mainstream colleagues.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.343
Threshold uncertainty score0.690

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.003
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.062
GPT teacher head0.326
Teacher spread0.264 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations10
Published2000
Admission routes3
Has abstractyes

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