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Record W7038162293

FEMALE ISLAMIC SCHOOL TEACHERS IN ONTARIO: PERCEPTIONS OF EXPERIENCES AND PRACTICES

2007· article· en· W7038162293 on OpenAlexaboutno aff

Bibliographic record

VenueScholarship@Western (Western University) · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Watershed Management Studies
Canadian institutionsnot available
Fundersnot available
KeywordsIslamPerceptionSchool teachersNarrativePower (physics)Narrative inquiryEquity (law)Grounded theory
DOInot available

Abstract

fetched live from OpenAlex

This study uses grounded theory methodology to analyse the narratives of four female Ontario Islamic school teachers who could work where financial benefits are better and dress codes are less restrictive. This study also examines the teachers’ experiences with and perceptions of gender equity within their Islamic school. While the participants’ narratives indicate, as feminist debates have done, that Muslim women’s perspectives are not monolithic, the teachers agree on three issues. Firstly, they face a power struggle with members of the community due to the school’s limited resources. Secondly, the women agree on the behaviours that are inappropriate when interacting with the opposite sex. Finally, the participants believe that the school’s power dynamics have resulted in gender inequity for female Islamic school teachers seeking administrative roles. An examination of Ontario's Islamic schools will determine whether this study’s findings are common among the province's female Islamic school teachers.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.223
Threshold uncertainty score0.449

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0130.006
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.001
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 head0.058
GPT teacher head0.311
Teacher spread0.253 · 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

Citations0
Published2007
Admission routes1
Has abstractyes

Explore more

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