Identity construction of young Muslim students attending Islamic schools in Winnipeg
Bibliographic record
Abstract
The Muslim identity of young people attending independent Islamic schools in Winnipeg is the central focus of this thesis. More specifically, the study focuses on how young people construct their Muslim identity at the crossroads of Canadian culture and a minority religious heritage, in independent schools where Islam is dominant. Three main objectives guide this research: a) The markers of Muslim identity as presented by the young participants; b) the role of Islamic schools in the process of identity construction of young people; c) the relationships of young people with their religious and cultural heritage in a non-Muslim majority context. The conceptual framework consists of four main concepts: the concept of identity and its religious construction in a diasporic context; Bourdieu's religious habitus as a theoretical basis for the analysis of identity choices of young Muslims; Islam and the concept of the community as a sociological analysis; and the role of the school and the family in the construction of identity of young Muslims. From a scientific perspective, this is the first comprehensive work on the construction of Muslim identity for young immigrants living in Winnipeg and attending Islamic independent schools. Through the study of youth attending Islamic schools in Winnipeg, the tools of qualitative methods of data collection were adopted, ie group discussions and individual interviews. The data analysis framework looks at participants’ historical and relational journeys as they negotiate their identity in three identity poles: the legitimizing identity of the dominant internal discourse, the resistant identity, and the identity-project that these youth build. The results show a strong attachment of young people to their religion and an active participation in the construction of their Muslim identity. Through the burden of the dominant majority culture, these young people negotiate their identities from three different religious perceptions: an inherited family Islam, a reconstructed Islam, and a renewed Islam. The intent of the thesis is to contribute to the advancement of knowledge in the study of religious minorities in Canada, including young people attending Islamic denominational schools.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.005 |
| 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".