Bibliographic record
Abstract
The Islamic Studies Library (ISL) was founded in 1952 in conjunction with the Institute of Islamic Studies (IIS). The founder, Dr. Wilfred Cantwell Smith, persuaded Principal F. Cyril James in 1951 that the study of Islam at McGill University was a worthwhile pursuit. From 1952 to the present, the ISL has grown from a modest 250 books to a collection of over 150, 000 volumes. The Library works to highlight and illustrate the breadth of Islamic civilization. This paper examines the ISL’s growth and evolution in its 60 years of existence.ResuméLa Bibliothèque d’études islamiques (BEI) fut fondée en 1952 en conjonction avec l’Institut d’études islamiques (IEI). Le fondateur, le docteur Wilfred Cantwell Smith, a persuadé le Principal F. Cyril James en 1951 qu’il serait souhaitable que les études islamiques deviennent un domaine d’activité à l’Université. Dotée en 1952 d’une modeste collection de 250 livres, la BEI possède aujourd’hui plus de 150 000 volumes. La Bibliothèque vise à mettre en relief et à illustrer l’ampleur de la civilisation islamique. Cet article examine la croissance et l’évolution de la BEI au cours de ses 60 années d’existance.
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
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Not applicable | medium |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Qualitative | medium |
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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.008 | 0.018 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.020 | 0.011 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.037 | 0.011 |
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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".