Bibliographic record
Abstract
Nigosian (Univ. of Toronto) has written a remarkable book. Though one might quibble over the omission of any meaningful discussion of fiqh (at least it's in the glossary) or object to glib treatment of some rather controversial topics (the influence of the Night Journey and Ascension literature on Dante is not as cut and dried as the author repeatedly asserts), this panoramic overview of Islam is refreshing in its conciseness and logical order of presentation. Succinct discussions of complicated topics, such as the origins and development of Shi'ism, the causes of Ottoman decline, the phenomenon of jihad, moral and social behavior of Muslims, women's religious duties, Islamic feminism, and observances and festivals, all merit especial praise. In addition, there is a seminal theological comparison of Islam to Christianity (normally not included in a work such as this), a discussion that does not gloss over important differences or sugarcoat the rough edges that religious traditions often exhibit. There are a few misstatements of fact (the third surah of the Qur'an is not entitled Ali Imran). The occasional typographical errors, appearing mostly in relation to the author's own system of transliteration, are relatively minor. Summing Up: Highly recommended. General readers and lower-level undergraduates.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.109 | 0.032 |
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".