An Exploration of the Muslim Diaspora in Toronto Public Schools
Bibliographic record
Abstract
Abstract: This paper is an introductory study of the diaspora of Muslim students in Toronto public schools. There has been a tendency in modern discourses to address Muslims as monolithic. Such a limited understanding of this ethnoreligious group fails to recognize the diverse cultural and racial heterogeneity that exists among Muslims. To highlight diversity among Muslim students, pooled cohort data from the 2017 Toronto District School Board (TDSB) Student Census and TDSB administrative records were used to explore the wide range of Muslim-identifying students’ racial/ethnic background, languages spoken, region of birth, and year of arrival in Canada. We noticed that the constructed homogenized identity of Muslims in Canada is entirely inaccurate and we decided to take advantage of the unique nature of the data, which allows us to present a new alternative perspective on how we should understand identity construction of Canadian youth, specifically those with intersectional backgrounds. At the time of writing, these data are the only of their type that allow for a detailed analyses of race and religious affiliation with a sizeable Muslim subpopulation in Canada. We believe that the uniqueness of this data which considers variables such as religious affiliation, region of birth, and first language spoken in the home provides us with the unique opportunity to explore the nuance identity of Muslim youth. Résumé: Cet article constitue une étude introductive sur la diaspora des éléves musulmans au sein des écoles publiques de Toronto. Les discours contemporains présentent les musulmans comme un groupe monolithique. Une telle vision réductrice de ce groupe ethnoreligieux ne permet pas de saisir la diversité culturelle et raciale qui le caractérise. Afin de mettre en lumiére cette hétérogénéité chez les éléves musulmans, nous avons exploité des données regroupées provenant du Recensement des éléves de 2017 du Conseil scolaire du district de Toronto ainsi que des dossiers administratifs du même Conseil. Ces données ont permis d’explorer la pluralité des origines raciales et ethniques, des langues parlées, des régions de naissance et des années d’arrivée au Canada des éléves s’identifiant comme musulmans. Nos analyses révélent que l’identité homogénéisée qui est souvent attribuée aux musulmans au Canada est profondément inexacte. En tirant parti de la spécificité de ces données, nous proposons une perspective alternative sur la maniére d’appréhender la construction identitaire des jeunes Canadiens, en particulier ceux issus de trajectoires intersectionnelles. À ce jour, il s’agit des seules données de ce type permettant une analyse détaillée croisant race et affiliation religieuse auprés d’une sous-population musulmane significative au Canada. Nous estimons que la richesse de ces données qui intégrent des variables telles que l’affiliation religieuse, la région de naissance et la langue premiére parlée à la maison, offre une occasion unique d’explorer la complexité et la nuance de l’identité des jeunes musulmans.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".