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Record W4388771241 · doi:10.1515/9781552384046

Missing Pieces

2007· book· en· W4388771241 on OpenAlexaboutno aff
Olga Barsony-Verrall

Bibliographic record

VenueUniversity of Calgary Press eBooks · 2007
Typebook
Languageen
FieldArts and Humanities
TopicOral History, Memory, Narrative Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsGeologyComputer science

Abstract

fetched live from OpenAlex

"Her story adds to the growing literature related to individual life stories of Holocaust survivors. There is much we can learn from her book." - Benjamin Schlesinger, Professor Emeritus, University of Toronto Until age seven, Olga Barsony Verrall lived an idyllic life in Szarvas, a small town in Hungary, surrounded by her doting, observant Jewish family. After the Nazi invasion in 1944, Olga found herself, along with most of her family, interned in the Auspitz (Hustopece) labour camp. Eventually reunited after the war, the family returned to Szarvas, only to face a different kind of oppression at the hands of the new Communist government. After immigrating to Winnipeg in 1957, Olga met and married Orland Verrall, the cantor at Rosh Pina synagogue. Together they built a new life in Canada and soon welcomed two daughters, Judy and Lesley. Yet Olga continued to be haunted by her past. Though she was very young during her time in the camp, Olga had vivid and painful memories of the horrifying things she had seen and experienced there. A nagging sense of emptiness and anger stayed with her all her life. After her beloved husband Orland passed away, her emotional state became increasingly fragile, and she became dependent on prescription drugs to numb her pain. A long journey of physical and mental healing, along with the support of her family, helped Olga piece her life back together. For Olga, writing her memoir was a catharsis. For her readers, it will be an inspiration.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.643
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.043
GPT teacher head0.204
Teacher spread0.161 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2007
Admission routes1
Has abstractyes

Explore more

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