Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".