Bibliographic record
Abstract
A beautiful building at the entrance to the Rehavia neighborhood in Jerusalem, named "Villa Leah," is a monument to an unusual love story from the early twentieth century -one that gives us insight into discrete social realities of the "Holy City" apart from oftrepeated historical narratives.Nassib Bey Abcarius, the grandson of an Armenian bishop, born in Beirut, arrives in Jerusalem after years studying law in Paris, working for the British army in Cairo, and becoming a judge in Khartoum, and enjoys a lucrative career as a private lawyer.At the age of 54, he falls in love with Leah Tennenbaum, the daughter of a Jewish real estate agent.During World War I, the teenaged Leah had become a focus of celebrity scandal, as the reputed concubine of Cemal Pasha, the Ottoman ruler of Greater Syria.After the war, she had a brief marriage to an officer in Britain's Jewish Legion with whom she had a son, and returned to Jerusalem after her divorce.Nassib and the 30-year-old Leah wed in Paris in a civil marriage, settled in Jerusalem and quickly had two daughters.Five years into the marriage, the Bauhaus-styled Villa Leah was inaugurated but the couple lived in it only a few short years before Leah escaped with her children to Cairo in 1937, never to return.She died in 1967 in Montreal, surviving Nassib by twenty-one years.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.030 | 0.009 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.008 | 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".