Bibliographic record
Abstract
This paper investigates the post-conversion coping strategies of ten White converts to Islam in a predominantly Canadian context. The participants were interviewed in 2023 using a semi-structured interview guide. There are very few studies of Canadian converts to Islam, and none that look at coping strategies. Following Pargament, I do a thematic analysis of the data and investigate the participants’ religious and non-religious coping strategies of the stressors resulting from their conversion to Islam. White converts sit at an illuminating nexus of “race” and religion in Canada – their whiteness makes them part of the dominant majority, but their Muslimness excludes them. White converts, especially women who wear hijab, experience racialisation and discrimination after conversion. They are both welcomed and distrusted by a Muslim community that, due to their experiences of European colonisation, laurels and dislikes Whiteness. The main coping strategies mentioned by the participants are religious, advocacy, and avoidance. A typical strategy of social support was less commonly mentioned due to their post-conversion experiences of being estranged from their family and friends and difficulties settling into Muslim communities.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".