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Exploring Islam from an American Perspective: A Study of the Views of McGill University Alumni in Indonesia

2025· article· en· W4411113748 on OpenAlexaboutno aff
Anis Saidah, Firdah Ni’matus Sholihah, Iksan Iksan

Bibliographic record

VenueUrwatul Wutsqo Jurnal Studi Kependidikan dan Keislaman · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Islamic Studies
Canadian institutionsnot available
Fundersnot available
KeywordsIslamPerspective (graphical)SociologyPolitical scienceMedia studiesTheologyArtVisual artsPhilosophy

Abstract

fetched live from OpenAlex

This study aims to explore the dynamics of Islamic studies from a Western perspective, through the views of Indonesian alumni who have studied at McGill University, Canada. Using a qualitative approach and case study design, this research explores how cross-cultural academic experiences can shape a more critical, contextual, and interdisciplinary understanding of Islam. The main focus of this study is the paradigm shift in Islamic studies in the West, which was initially dominated by orientalism, towards a more open and dialogical scientific approach. Based on in-depth interviews with three McGill alumni who are actively involved in academics and religious activities in Indonesia, the findings suggest that McGill University plays a significant role in shaping reflective Islamic thought, adaptive to social realities, and supporting moderate values such as democracy, human rights, and pluralism. The implications of these findings are crucial for the development of Islamic studies in Indonesia, offering an approach that is more inclusive and relevant to Indonesia's social and cultural dynamics

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.109
Threshold uncertainty score0.218

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0190.008
Scholarly communication0.0070.002
Open science0.0010.005
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0030.000

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 head0.078
GPT teacher head0.348
Teacher spread0.270 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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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