Bibliographic record
Abstract
This most recent, and comprehensive compendium, on the subject of the architecture of Islam sheds light on the subject materials. New information on well-known historical examples, the inclusion of historical examples not usually (if ever covered) in such scholarship and an expansion of analysis with respect to modern and contemporary case studies of Islamic religious spaces all underscore the scholarly contribution of this two-volume set. By including such a range of buildings examined, by a large number of scholars from various backgrounds, the compendium effectively recasts the direction of scholarship in this field in a manner that is neither linear or hierarchical.This two-volume set includes 58 essays on a range of regionally-specific examples of architecture from the Islamic world. The first volume of The Religious Architecture of Islam focusses on Asia and Australia, and the second volume focusses on Africa, Europe and the Americas. The volumes are organized in a non-chronological manner, with essays grouped by geographical region covering materials directly related the understanding of religious architecture of Islam.In Volume I, there are four sections with a total of 32 essays written by 29 different scholars. The four sections are: Background themes, West and Central Asia, South and East Asia and Australia.In Volume II, there are four sections with a total of 26 essays written by 20 different scholars. The four sections are: Al-Andalus and the Maghrib, Africa and Sicily, Europe and the Americas.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".