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Record W2921177037 · doi:10.5508/jhs.2018.v18.a10

Remembering Three Nehemiahs in Late Second Temple Times: Patterns and Trajectories in Memory Shaping

2018· article· en· W2921177037 on OpenAlexaffvenue
Ehud Ben Zvi, Sylvie Honigman

Bibliographic record

VenueJournal of Hebrew Scriptures · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicBiblical Studies and Interpretation
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsFocus (optics)Generative grammarSet (abstract data type)Period (music)TempleHistoryAestheticsCognitive scienceLiteratureArtPsychologyPhilosophyLinguisticsComputer scienceAncient history

Abstract

fetched live from OpenAlex

This article explores the workings of a set of memory-shaping patterns that were influential in the construction of Nehemiah as an evolving site of memory during the late Second Temple period. Its main focus is on the three Nehemiahs of memory evoked in and encountered by readers of the three main sources that shaped memories of the Nehemiah: Ezra-Neh, Sirach, and 2 Macc. The article’s focus is on the generative pattern that scripted expectations about how good kings should behave, and which played an important role in the way memories of Nehemiah were constructed and communicated by these texts.

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)0.005
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 score0.008
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0050.011
Scholarly communication0.0050.004
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.051
GPT teacher head0.264
Teacher spread0.214 · 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

Citations1
Published2018
Admission routes2
Has abstractyes

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