Bibliographic record
Abstract
Abstract The Muslim Student Association of the United States and Canada (MSA) was founded in 1963, at the University of Illinois at Urbana-Champaign by a group of students from eleven universities. Established by immigrant Muslim students, the MSA initially focused on unifying Muslim students under a pan-Islamic identity and reviving Islamic orthodoxy. In the initial two decades, the number of MSA chapters increased swiftly, and the organization’s diverse membership, professional needs, and the growing Muslim community in North America gave rise to various other affiliated organizations, such as the Islamic Society of North America. Over time and in some cases, membership in MSAs has lent itself to challenges and tensions around ethnic, racial, and gender lines, resulting in the formation of separate organizations by members seeking more specific representation. Many MSAs have adapted to include more diverse needs and perspectives, especially as its membership increasingly included American-born Muslims. Post-9/11, MSAs faced scrutiny and increased demands for representation, which led them to focus more on American identity and local activism, while still addressing basic needs of Muslim students on campus. In recent years, MSAs continued to adapt, incorporating social justice issues, mental health awareness, and professional interests into their programming. In the 2020s, there were more than six hundred MSAs across college campuses, and the organization remains a crucial platform for Muslim students, though its focus and activities vary widely depending on the campus context and the evolving needs of its members.
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 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.032 | 0.001 |
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".