International Summer School on Islam and Science ( Paris , 22 - 31 August 2014 )
Bibliographic record
Abstract
An excellent program on Islam and Science was co-organised by Professors Nidhal Guessoum and Jean Staune (Director, Universitie Interdisciplinaire de Paris) in Paris for 21 Muslim ‘students’ from universities and institutions in Algeria, Egypt, Jordan, France, the United Arab Emirates, the United States and the United Kingdom, Indonesia and Malaysia. Professorial lectures were delivered by prominent Muslim scientists/engineers/religious scholars – Nidhal Guessoum (American University of Sharjah, UAE), Ehab Abouheif (McGill University, Canada), Bruno Guiderdoni (Islamic Institute of Advanced Studies in Paris), Odeh Jayyousi (Jordan), Usama Hasan (Quilliam Foundation, UK) and leading Christian scientists – Philip Clayton (Claremont School of Theology, USA), Denis Alexander (Faraday Institute, Cambridge, UK) and Jean Staune. This was a cutting edge program on the state of thinking on critical issues regarding Religion and Science. To support the training, group visits were made to the impressive institutions of the Museum National d’Histoire Naturelle and the Cite des Sciences et de l’Industrie, as well as to the Central Paris Masjid. The program was not all scientific as participants were also treated socially to warm French hospitality and delicious cuisine for their lunches and dinners.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.260 | 0.081 |
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".