Bibliographic record
Abstract
Abstract Mosques refer to the Muslim house of worship, signifying the gathering place for Muslims to fulfill their obligation of communal prayer. Mosques in the United States and Canada are distinct from mosques in Muslim-majority countries in two different ways. Mosques in the United States and Canada are congregations, which means that the mosque is run by a group of participants; in Muslim-majority countries, mosques are controlled by the state of wealthy patrons. Second, mosques in the United States and Canada are a place of worship and a center of various community activities; in Muslim-majority countries, the mosque is often simply a place of worship. The first era in the history of mosques in North America was from 1890 to 1964. Starting in the 1920s, mosques were established in the United States and Canada by Muslim immigrants. Owing to the relatively small number of Muslim immigrants, few mosques were founded before the 1960s. African Americans started becoming Muslim in the 1920s and started establishing mosques in the 1930s. The number of their mosques was also few. The second era is from 1965 to 2023. This period marks the tremendous increase in the number of Muslim immigrants and African American converts to Islam, and as a consequence, the number of mosques has risen significantly. In 2020, there were 2,769 mosques as compared with 498 in 1984. Mosques in 2020 were healthy: they were growing in number, participants, and activities. Mosques were also very much involved in American society and therefore did not evince a position of isolation and deep hostility to American society. In fact, studies show that mosques are a conduit for Muslims to become more civically engaged. However, the perceived disconnect between young adults and women constitutes a danger to the future of mosques in North America.
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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".