Bibliographic record
Abstract
Dar al-Islam is the realized vision of an American-born Muslim, an AmericaneducatedSaudi businessman, the award-winning architect Hassan Fathy(1900-89). The purpose-built educational center and mosque was built in theearly 1980s, sits in New Mexico’s mesa landscape, and today functions as aneducational retreat.During the late 1970s Abdullah Nurdin Durkee and his wife Nura envisionedthe construction of an Islamic village in the United States. During atrip to Makkah they met Sahl Kabbani, a Saudi businessman educated in theUnited States who felt a connection and desired to contribute in some manner.Together they decided to create an Islamic village that would also function asan educational center and retreat. Later on Nura Durkee, while also prayingin Makkah, met Mothie and Johara, daughters of the Saudi king at the time,both of whom offered a financial gift to start the project. The group searchedfor a suitable site and eventually settled on Abiquiu, NM, due to the abundanceof available land for a relatively low cost, the remote location, and the landscape’ssimilar qualities with those in the Middle East.In Abiquiu, 3,450 hectares were purchased in the rugged backcountry,populated with flat-topped mesas and a verdant valley near the Chama river.Abdullah Naseef, then rector of the King Abdul Aziz University in Jeddah, ...
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.016 | 0.006 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.021 | 0.003 |
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".