Bibliographic record
Abstract
<JATS1:p>The Cairo Genizah is considered one of the world’s greatest Hebrew manuscript treasures. Yet the story of how over a quarter of a million fragments hidden in Egypt were discovered and distributed around the world, before becoming collectively known as “The Cairo Genizah,” is far more convoluted and compelling than previously told. The full story involves an international cast of scholars, librarians, archaeologists, excavators, collectors, dealers and agents, operating from the mid-nineteenth to the early twentieth century, and all acting with varying motivations and intentions in a race for the spoils.</JATS1:p> <JATS1:p>Basing her research on a wealth of archival materials, Jefferson reconstructs how these protagonists used their various networks to create key alliances, or to blaze lone trails, each one on a quest to recover ancient manuscripts. Following in their footsteps, she takes the reader on a journey down into ancient caves and tombs, under medieval rubbish mounds, into hidden attic rooms, vaults, basements and wells, along labyrinthine souks, and behind the doors of private clubs and cloistered colleges. Along the way, the reader will also learn about the importance of establishing manuscript provenance and authenticity, and the impact to our understanding of the past when either factor is in doubt.</JATS1:p>
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 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.014 | 0.033 |
| Scholarly communication | 0.013 | 0.007 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".