Bibliographic record
Abstract
Autobiographical impostures, once they come to light, appear to us as outrageous, scandalous. They confuse lived and textual identity (the person in the world and the character in the text) and call into question what we believe, what we doubt, and how we receive information. In the process, they tell us a lot about cultural norms and anxieties. Burdens of Proof: Faith, Doubt, and Identity in Autobiography examines a broad range of impostures in the United States, Canada, and Europe, and asks about each one: Why this particular imposture? Why here and now? Susanna Egan’s historical survey of texts from early Christendom to the nineteenth century provides an understanding of the author in relation to the text and shows how plagiarism and other false claims have not always been regarded as the frauds we consider them today. She then explores the role of the media in the creation of much contemporary imposture, examining in particular the cases of Jumana Hanna, Norma Khouri, and James Frey. The book also addresses ethnic imposture, deliberate fictions, plagiarism, and ghostwriting, all of which raise moral, legal, historical, and cultural issues. Egan concludes the volume with an examination of how historiography and law failed to support the identities of European Jews during World War II, creating sufficient instability in Jewish identity and doubt about Jewish wartime experience that the impostor could step in. This textual erasure of the Jews of Europe and the refashioning of their experiences in fraudulent texts are examples of imposture as an outcrop of extreme identity crisis. The first to examine these issues in North America and Europe, Burdens of Proof will be of interest to scholars of life writing and cultural studies.
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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 | 0.014 | 0.069 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.008 | 0.026 |
| Scholarly communication | 0.023 | 0.025 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.012 | 0.015 |
| Insufficient payload (model declined to judge) | 0.066 | 0.021 |
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".