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Record W2968314954 · doi:10.30965/21967954-00903007

Mapping Jewishness in Antiquity

2018· article· en· W2968314954 on OpenAlexaff
John Van Maaren

Bibliographic record

VenueJournal of ancient Judaism · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicJewish and Middle Eastern Studies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsEthnic groupScholarshipAgency (philosophy)JudaismMacroSociologyIdentity (music)Field (mathematics)Social identity theoryLate AntiquityFunction (biology)Social scienceAnthropologyHistoryAestheticsPolitical scienceSocial groupClassicsPhilosophyComputer scienceArchaeologyLawMathematics

Abstract

fetched live from OpenAlex

This article introduces a recent contribution to the study of ethnicity from the social sciences that provides needed systemization to the study of Jewishness in antiquity. Current scholarship on Jewishness has no instrument by which to relate the construction of Jewish identity to macro-level societal changes. The current model, based on extensive empirical data, explains changes in the form and function of ethnicity by a cyclical model that links macro-level characteristics of the social field with individual agency in ethnic construction to produce the first comparative analytic of “how and why ethnicity matters in certain society and contexts.” The introduction presented here illustrates the various components of the model with examples from Jewish history and texts and suggests how this model might be used to better understand dynamics of identity construction and change among Jews in antiquity.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.038
Threshold uncertainty score0.075

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.044
GPT teacher head0.320
Teacher spread0.276 · 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 designTheoretical or conceptual
Domainnot available
GenreEmpirical

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
Published2018
Admission routes1
Has abstractyes

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