Bibliographic record
Abstract
Acknowledgments Note on Transliteration1. An Institutional Approach to the Politics of Western Muslim Minorities, by Adulkader H. Sinno, Indiana University Part 1. Western Muslims and Etablished State-Religion Relations 2. Claiming Space in America's Pluralism: Muslims Enter the Political Maelstrom, by Yvonne Yazbeck Haddad, Georgetown University and Robert Stephen Ricks, Georgetown University 3. The Practice of Their Faith: Muslims and the State in Britain, France, and Germany, by J. Christopher Soper, Pepperdine University and Joel S. Fetzer, Pepperdine University 4. Religion, Muslims, and the State in Britain and France: From Westphalia to 9/11, by Jorgen S. Nielsen, University of BirminghamPart 2. Western Muslims and Political Institutions 5. Muslim Underrepresentation in American Politics, by Abdulkader H. Sinno, Indiana University 6. Muslims Representing Muslims in Europe: Parties and Associations after 9/11, by Jytte Klausen, Brandeis University 7. Muslims in UK Institutions: Effective Representation or Tokenism? by Abdulkader H. Sinno, Indiana University and Eren Tatari, Indiana UniversityPart 3. Institutional Underpinnings of Perceptions of Western Muslims 8. How Europe and Its Muslim Populations See Each Other, by Jodie T. Allen, Pew Research Center and Richard Wike, Pew Research Center 9. Public Opinion toward Muslim Americans: Civil Liberties and the Role of Religiosity, Ideology, and Media Use, by Erik C. Nisbet, Cornell University, Ronald Ostman, Cornell University,and James Shanahan, Cornell University 10. The Racialization of Muslim Americans, by Amaney Jamal, Princeton UniversityPart 4. Western Muslims, Civil Rights, and Legal Institutions 11. Canadian National Security Policy and Canadian Muslim Communities, by Kent Roach, University of Toronto 12. Counter-Terrorism and the Civil Rights of Muslim Minorities in the European Union, by Anja Dalgaard-Nielsen, Danish Institute for International Studies 13. The Preventive Paradigm and the Rule of Law: How Not to Fight Terrorism, by David Cole, Georgetown University 14. Recommendations for Western Policymakers and Muslim Organizations, by Abdulkader H. Sinno, Indiana UniversityList of Contributors Index
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 | 0.001 | 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 | 0.006 | 0.006 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".