I Introduction: The making of a documentary corpus
Bibliographic record
Abstract
The making of a documentary corpusThe Ḥaram al-sharīf corpus from Jerusalem with its 980 documents is a collection of outstanding importance for the history of pre-Ottoman Western Asia.As will be discussed below, numerous editions have been undertaken and these documents have proven to be of pivotal importance, especially for the field of Mamluk Studies.Yet how and when these documents converged into a single corpus is still largely unexplored.Even its (scholarly) discovery, which began in the 1970s, has been a convoluted process.The first batch of documents came to light in August 1974 and some two years later, in October 1976, another, larger batch was discovered.65The present work is the catalogue of a third batch of these documents that was discovered in the late 1990s.The first two batches, catalogued by Donald Little in his 1984 Catalogue of the Islamic Documents from al-Ḥaram aš-Šarîf in Jerusalem, came to light in rather undramatic circumstances; they were simply lying in the drawers of modern display cases in the Islamic Museum on the Ḥaram al-sharīf.As described in this catalogue's preface, the main protagonists in the bringing of the documents to the attention of the scholarly community in the late 1970s and early 1980s were Amal Abul-Hajj, Linda Northrup and Donald Little.66Of particular importance for the subsequent scholarly work were the black and white photographs of the documents taken by Martin Lyons in 1978.These photographs were subsequently microfilmed and made available to the wider community to serve as the basis for almost all publications in the next decades.67Yet notes accompanying the documents show that they had in fact already been 'discovered' at least once before the 1970s: A member of the museum staff must have started to work on some documents before the 1970s as is evident from notes on papers that have regrettably since been lost.68Unfortuntely for researchers, who love narratives of discovery, the third batch (or new corpus) described in this catalogue was found (or rather identified) in a similarly unspectacular location: the cupboard of an office in the museum.Even though this new corpus came to light in the late 1990s, its documents have thus far hardly played a role in scholarship and the mere fact of its existence was not known 65 Little, Catalogue, 1984, 1. 66 Northrup/Abul-Hajj, Collection of Medieval Arabic Documents; Little, Catalogue.On Donald Little see the volume dedicated to his memory, Massoud, Studies in Islamic Historiography.67 The 1978-set was deposited at McGill University and most editions until well into the 2010s de facto relied on (microfilm) copies of these images.
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
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.078 | 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; both teacher heads agree on what is shown here.
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".