Bibliographic record
Abstract
How do Muslims make places in the Canadian Arctic? What helps them feel at home in surroundings where Islamic ritual practices are – besides many other challenges – complicated by extreme changes in daylight? In recent years, several purpose-built mosques have been built in the Canadian Territories. The construction of these mosques has been driven by wishes for rootedness, visibility, and – most importantly – the desire to feel home. The mosque hereby fulfills different functions: It provides a community home for gatherings, celebrations, and educational and leisure activities; a spiritual home and safe space for individuals; and a place of interaction with the local population. The new mosque communities are highly heterogeneous, raising not only questions of religious authority and the interpretation of Islamic traditions, but also of community building and belonging. This qualitative study looks at how Muslim newcomers relate to the Arctic environment with its distinct historical, socio-economic and -political context, such as their reasons for migrating north and staying, how they navigate differences and diversity and what their perceptions of home and belonging look like. Furthermore, it looks specifically at Muslim-Indigenous relations and interactions. Theoretically, the study is informed by critical northern geographies, the anthropology and sociology of Islam, geography of religion as well as spatial concepts. Findings are based on fieldwork from Inuvik and Yellowknife drawing on archival materials, literature, media, and semi-structured interviews with local community members. By foregrounding the lived experience of Muslims in the Arctic, it tackles stereotypes and misconceptions and illuminates the expansive spectrum of Muslimness. The focus on the study of Islam in rural and northern settings in Canada has been a void in the study of Islam in the West so far.
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 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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".