MétaCan
Menu
Back to cohort

Jewish Film Festivals

2025· reference-entry· en· W4412629227 on OpenAlexaboutno aff
Janis Plotkin, Olga Gershenson

Bibliographic record

VenueOxford University Press eBooks · 2025
Typereference-entry
Languageen
FieldSocial Sciences
TopicJewish and Middle Eastern Studies
Canadian institutionsnot available
Fundersnot available
KeywordsJudaismArtHistoryGenealogyArchaeology

Abstract

fetched live from OpenAlex

Abstract This chapter examines Jewish film festivals as a significant cultural phenomenon that has reshaped Jewish identity and practice since the 1980s. Beginning with the founding of the San Francisco Jewish Film Festival in 1981, the chapter traces how these festivals emerged during a period when American Jews sought alternatives to traditional religious institutions, creating new forms of secular Jewish observance and community. Through case studies of pioneering festivals in San Francisco, New York, Boston, Washington, DC, Seattle, Pittsburgh, Toronto, Berlin, Brussels, London, Melbourne, and Sydney, the chapter demonstrates how Jewish film festivals came up alongside other identity-based festivals but grew into a distinct and thriving movement. The analysis reveals distinct developmental phases: pioneering efforts in the 1980s, global expansion in the 1990s, regional growth and professionalization in the 2000s, and emerging challenges from streaming and changing audience engagement in the 2010s onward. The chapter examines the festivals’ impact on independent Jewish cinema, their role in fostering networks among programmers and filmmakers, and their navigation of ongoing political controversies. Drawing on primary sources from festival archives, interviews with founders, and existing scholarship, this chapter offers the first comprehensive overview of Jewish film festivals as platforms that both reflect and actively shape contemporary Jewish culture.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.002
Scholarly communication0.0030.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0160.002

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 head0.041
GPT teacher head0.266
Teacher spread0.225 · 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
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueOxford University Press eBooksSame topicJewish and Middle Eastern StudiesFrench-language works237,207