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Record W2045979799 · doi:10.1017/s0364009405470178

Ofira Seliktar. <i>Divided We Stand: American Jews, Israel, and the Peace Process.</i> Westport, CT: Praeger, 2002. xvi, 272 pp.

2005· article· en· W2045979799 on OpenAlexaff
Harold M. Waller

Bibliographic record

VenueAJS Review The Journal of the Association for Jewish Studies · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicJewish and Middle Eastern Studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsDiasporaHomelandIndependence (probability theory)JudaismState (computer science)The HolocaustGovernment (linguistics)Jewish statePolitical scienceHistoryLawDeportationReligious studiesAncient historyEconomic historyPolitical economySociologyPoliticsArchaeologyImmigrationPhilosophy

Abstract

fetched live from OpenAlex

Israel, and before that the idea of a Jewish state in the traditional homeland, has long captured the imagination of many, if not always most, American Jews. The close connection between Jews in Israel and the United States intensified as the events of the last century unfolded, especially the Holocaust, the struggle for Israel's independence, and then the unending effort to safeguard that independence and ensure security. The 1967 Six-Day War, the run-up to which conjured up images of another calamity, had a profound effect in the Diaspora, driving home the reality of Israel's precarious security and the state's central importance in modern Jewish life. That watershed produced a relatively short-lived period when it seemed that American Jews were united in their support for Israel. But, since 1977, that “sacred unity” has been called into question as sharp divisions have appeared—exacerbated by controversial Israeli government decisions and the pressures of the peace process since 1991.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.026
Threshold uncertainty score0.087

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0020.001
Scholarly communication0.0020.004
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0260.010

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.

Opus teacher head0.028
GPT teacher head0.333
Teacher spread0.304 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2005
Admission routes1
Has abstractyes

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