Bibliographic record
Abstract
WINNER of the Association of Jewish Libraries’ Judaica Reference Award Provides critical overviews of the main writers and key themes of Anglophone Jewish fiction This collection of essays represents a new departure for, and a potentially (re)defining moment in, literary Jewish Studies. It is the first volume to bring together 28 chapters covering a wide range of American, British, South African, Canadian and Australian Jewish fiction. The volume is divided into 3 parts – American Jewish Fiction; British Jewish Fiction; and International and Transnational Anglophone Jewish Fiction – but many of the essays cross over these boundaries and speak to each other implicitly, as well as, on occasion, explicitly. Extending and redefining the canon of modern Jewish fiction, the volume juxtaposes major authors with more marginal figures, revising and recuperating individual reputations, rediscovering forgotten and discovering new work, and in the process remapping the whole terrain. This volume opens windows onto vistas that previously had been obscured and opens doors for the next generation of studies that could not proceed without a wide-ranging, visionary empiricism grounding their work. Key Features Highlights the rich diversity of the field and identifies its key themes, including immigration, the Diaspora, the Holocaust, Judaism, assimilation, antisemitism and Zionism Analyses the main trends in Anglophone Jewish fiction and situates them in historical context Discusses the place of Anglophone Jewish fiction in relation to critical debates concerning transatlanticism and transnationalism; ethnicity and identity politics; postcolonial studies, feminist studies and Jewish Studies With a preface by Mark Shechner, the volume’s contributors include Vicki Aarons (Trinity University, Texas), Debra Shostak (Wooster College, Ohio), Ira Nadel (University of British Columbia), Efraim Sicher (Ben-Gurion University), Phyllis Lassner (Northwestern University), Sue Vice (University of Sheffield), Lori Harrison-Kahan (Boston College), Ruth Gilbert (University of Winchester), Beate Neumeier (University of Cologne) and Sandra Singer (University of Guelph)
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.041 | 0.014 |
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".