Mapping of Religious Moderation Literature in Higher Education: A Bibliometric Review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Religious moderation has become a critical focus in higher education, particularly in fostering social harmony and inclusive national identity. This study aims to analyze current trends in religious moderation research within the higher education sector and identify opportunities for future research development. A Systematic Literature Review (SLR) approach was utilized, guided by PRISMA protocols to ensure accuracy and relevance. A total of 160 publications were initially gathered from ERIC, Taylor Francis, and Mendeley databases indexed in Scopus. Based on defined inclusion criteria, 23 publications from 2019 to 2024 were selected for in-depth analysis. Bibliometric analysis was conducted using VOSviewer 1.6.20 software. Findings reveal fluctuating trends in religious moderation research, with a notable increase in publications during 2022, likely influenced by contemporary social issues and educational policies. Indonesia emerged as the leading contributor, followed by Jordan and Canada. Predominantly, qualitative and quantitative methodologies were employed. Thematically, research concentrated on radicalism, curriculum development, and religious tolerance. Density mapping further indicates a research gap in the exploration of nationalism within the context of religious moderation. The limited focus on nationalism suggests an opportunity for future research to bridge this gap and reinforce the role of religious moderation in cultivating inclusive national identity within higher education. This study underscores the need for continued and diversified research on religious moderation, emphasizing its potential to promote social cohesion and counter radical ideologies in academic environments.
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Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Bibliometrics Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Observational | high |
| gpt | Bibliometrics Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.014 | 0.061 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it