An Autoethnographic Exploration About Wearing/Not Wearing the Niqab in Early Childhood Education and Care Settings
Bibliographic record
Abstract
On October of 2018, the province of Quebec passed Bill 62 becoming the first Canadian province to ban the wearing of a face veil when providing and receiving publicly-funded services, including childcare. Literature examining the practice of face-veiling in workplace settings is limited if not non-existent. Scholarly literature examining the ‘burqa ban’ laws in European countries affirm the laws are based solely on neo-orientalist and postcolonial assumptions of face-veiled Muslim women with no empirical research supporting claims that face-veiled Muslim women pose a threat to the security of Western nations or Western values of secularism and gender equality. Yet, face-veiled Muslim women are being pushed towards unveiling in order to access public funded services and actively participate in the public sphere. This Master’s Research Paper (MRP) aims to explore the idea of wearing/not wearing the faceveiled early childhood education and Care settings (ECEC). Using an autoethnographic approach, I use my experiences working with young children to explore the equitable inclusion of face-veiled early childhood educators in ECEC settings. Keywords: Autoethnography, Niqab in the Early Childhood Education (ECE), Islamophobia in the workplace
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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 | 0.011 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.022 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".