Chimneys in the Night: A Comparative Analysis of Elie Wiesel’s Night and Olga Lengyel’s Five Chimneys
Bibliographic record
Abstract
This essay aims to evaluate some of the similarities and differences in the experiences of two Holocaust survivors, Olga Lengyel and Ellie Wiesel. The essay will explore the experiences of these two survivors in Auschwitz, Birkenau, and Buchenwald and examine why some of their experiences may have been different. The purpose of the essay is not to belittle the experiences of one gender or the other, but to identify how gender and sexuality made their experiences different. Wiesel’s and Lengyel's haunting memories of their experiences in these concentration camps offers a lense through which to examine the potential role that gender had on the experiences of the camp inmates. Both authors provide a graphic depiction of life in the concentration camp and the reader is taken into the depths of the hell in which these human beings were forced to live. Lengyel and Wiesel in a sense represent larger groups of people; women in the concentration camp and men in the concentration camp. Their memoirs exemplify the experiences of the millions of men and women who lived in the concentration camps, many of whom’s voices were silenced as a result of their presence in the camps. Therefore one can use the two accounts and the wealth of information within them to draw general conclusions about the experiences of each gender within the camp.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.012 | 0.011 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".