Book Review of Tamara Neuman, Settling Hebron: Jewish Fundamentalism in a Palestinian City
Bibliographic record
Abstract
Tamara Neuman has been researching Jewish ideological settlements for many years. She started her research in 1994, after the signing of the Oslo Accords. In Settling Hebron, Neuman presents the first critical ethnography of the Jewish settler populations in Kiryat Arba and the adjacent Jewish Quarter in the Old City of Hebron. This ethnography illustrates the changes that distinguish and define ideological settlements. Neuman examines how religion functions as ideology in the Palestinian city of Hebron, with a focus on Jewish settler expansion and its close but ambivalent relationship to the Israeli state. Through extensive fieldwork, interviews with settlers, soldiers, Palestinian residents as well as archival research, Neuman provides a fascinating and often disturbing account of a tense, abnormal co-existence between Palestinians and Jews in an occupied territory, populated mostly by Palestinians yet administered by Israeli soldiers.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 0.004 |
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".