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Muslim Student Associations in North America

2025· reference-entry· en· W4409408141 on OpenAlexaboutno aff
A. I. Mahbub Uddin Ahmed

Bibliographic record

VenueOxford Research Encyclopedia of Religion · 2025
Typereference-entry
Languageen
FieldSocial Sciences
TopicReligion, Society, and Development
Canadian institutionsnot available
Fundersnot available
KeywordsGeographyGenealogyPolitical scienceHistory

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.894
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.004
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.041
GPT teacher head0.387
Teacher spread0.346 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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