Bibliographic record
Abstract
The renowned Yiddish writers, brothers Isaac Bashevis and Israel Joshua Singer, shaped the modern understanding of Hassidic life before the Second World War. Their stories and autobiographies describe the Old Country from a male perspective with an emphasis on the Hassidic law court their father presided over. However, they minimize or ignore the female participants in their stories. Their mother, sister, grandmother, and women of the community are flat presentations who love the feeding their families, have little education, and have a narrow world view. Their description is not wrong, rather it’s incomplete. This study considers the importance of their oft-forgotten sister equally talented Yiddish writer Esther Singer Kreitman, in creating our understanding of this Hassidic life. While the Singers were masters in the Yiddish literary world well published and received, their sister has been overlooked until recently partially because of her own insecurities and because of the misogyny of the publishing world then. Some scholars have let her mental-health issues and their own anti-women ideologies influence their critiques, but most critics praise her work as insightful. Yet, her perceptions of the pre-World War II Polish Hassidic community are as valid as her brothers’.
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 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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.017 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".