Bibliographic record
Abstract
This new book is a study of Islam in the digital world, containing a collection of scientific articles written by 16 scholars about the increasingly interesting and complex phenomena of the global Islamic world. Most of the authors teach at various universities in the United States and Canada (North America), and the editor of this volume is Robert Rosehnal, Professor in the Department of Religion Studies and Founding Director of the Center for Global Islamic Studies at Lehigh University, Pennsylvania, USA. This interdisciplinary volume highlights cutting-edge research with unique perspectives and new insights into the evolving Islamic cyber landscape, presenting case studies from multiple geographic and cultural locations, and multiple languages (Arabic, Persian, Indonesian and Spanish). The main sources of the authors, the analysis and interpretation they use is digital multimedia technology. These “virtual texts” include websites, podcasts, blogs, Twitter, Facebook, Instagram, YouTube, online magazines and discussion forums, and religious apps. Websites and social media platforms are living “texts” that are constantly evolving, shrinking, changing, and even disappearing, leaving no trace. In this sense, this book needs to be seen as a portrait—or, rather, a screenshot—of the complex and deformed cyber world of Islam at some point in its ongoing evolution. This book explores widely the digital expression of various Muslim communities in cyberspace, or iMuslims, related to the world of imams, clerics, and Sufis, feminists and fashionistas, artists and activists, spiritualists and online influencers. Several articles map the diversity and vibrancy of Islamic digital media against the backdrop of broader social trends in particular hot issues affecting Muslims living in Western countries: racism and Islamophobia, gender dynamics, celebrity culture, identity politics, and fashions of piety, and changing religious practices. The case studies presented in this book cover a wide cultural and geographical area, namely Indonesia, Iran, the Arab Middle East, and North America.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.086 | 0.026 |
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".