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Record W3004971475

Reflections on Jewish Women in Eulogies and Sermons of Ottoman Sages in the Sixteenth to Eighteenth Centuries

2018· article· en· W3004971475 on OpenAlexvenueno aff
Ruth Lamdan

Bibliographic record

VenueWomen in Judaism A Multidisciplinary e-Journal · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicHistorical and Linguistic Studies
Canadian institutionsnot available
Fundersnot available
KeywordsJudaismTorahAmbivalencePrayerOttoman empireIdeal (ethics)HistorySociologyInheritance (genetic algorithm)ClassicsAncient historyGender studiesReligious studiesPsychologyLawPolitical scienceSocial psychologyPhilosophyArchaeology
DOInot available

Abstract

fetched live from OpenAlex

The article is based on sermons and eulogies delivered by preachers in various Jewish communities throughout the Ottoman Empire in the first 200-250 years following the expulsion from Spain, and the integration of the exiles from the Iberian Peninsula in the Ottoman region. Almost all the sages who were the heads of congregations and served as leaders in prayer, teachers and preachers in synagogues, were of Spanish descent, and their statements reflect the Sephardic influence on the Jews of the empire. Sermons and ethical (musar) literature, intended to guide and instruct the public about proper religious, social, and familial behavior, show the ambivalent attitude towards women in general, and the disparity between the rabbinic ideal and rabbinic practice. These sources must be viewed as mostly educational; their authors never challenge the traditional roles of women in society. However, they also encourage their community members to respect exemplary women in their families and social circles. The almost impossible image of the Woman of Valor is the focus. Nevertheless, the commentators also point out the merits of women in general, noting that women played an instrumental role in the Exodus from Egypt and other biblical events, and emphasize that women support Torah study, contribute to synagogues and charities.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.538
Threshold uncertainty score0.834

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.042
GPT teacher head0.375
Teacher spread0.332 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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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