Navigating Atheist Identities: An Analysis of Nonreligious Perceptions and Experiences in the Religiously Diverse Canadian City of Ottawa
Bibliographic record
Abstract
There is very little research that is empirically-based about atheism in Canada; this thesis seeks to contribute foundational knowledge in this area. It begins with a historical and contemporary overview of atheism in Canada by examining its appearance in government, law, and media. It then addresses the question: “How do atheists construct their identities in the context of a religiously diverse Canada?” through an analysis of data collected from participant-observation with an atheist university club, the Atheist Community of the University of Ottawa (ACUO), followed by an analysis of five significant themes which arose from forty life history interviews (twenty with ACUO members; twenty with Ottawa-area atheists who did not belong to an atheist community that met in person). These themes are: loss of religious identity and/or development of atheist identity; group belonging; perceptions of media and public understanding of atheism; the use of the United States for narrative or comparative purposes; and the frequency of receiving a negative reaction simply for being an atheist. This study found that most interviewees perceived the Canadian public and the media as not understanding atheism because the subject is not commonly reported on or discussed, and many said that (ir)religiosity rarely came up in conversations with strangers, acquaintances, or co-workers. These notions were often seen as resulting from a Canadian social etiquette which dictates that controversial subjects should be avoided in order to minimize the risk of causing offense. Moreover, members of the ACUO often said that they joined an atheist community because they wanted a safe space to meet like-minded people with whom they could freely discuss religion without causing offense to religious others. Unlike in findings from the United States, interviewees did not speak of their atheist identities as being considered ‘un-Canadian’ or as excluding them from their conception(s) of Canadian society. While interviewees often said they were selective with whom they decided to express their atheism, most felt quite positive about living as an atheist in Canada, especially compared to the plight of atheists living in other countries, and atheism came across as being ‘just’ another ‘idea’ in a mosaic of cultural ideas.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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".