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Record W7154315843 · doi:10.23777/sn.0120/art_tcho01

Post-Holocaust Migrations from Poland to America

2020· article· en· W7154315843 on OpenAlexaff
Thomas Chopard

Bibliographic record

VenueS I M O N Shoah Intervention Methods Documentation · 2020
Typearticle
Languageen
FieldPsychology
TopicMemory, Trauma, and Commemoration
Canadian institutionsCanadian Nautical Research Society
Fundersnot available
KeywordsJudaismThe HolocaustAgency (philosophy)RefugeeDisplaced personDeportation

Abstract

fetched live from OpenAlex

This article seeks to reconstruct the trajectory of a Polish Jewish family, the Cyngels, from their pre-war life up to their migration to America in the early 1950s, encompassing their various experiences of war (survival in Poland and the Soviet Union) and of the aftermath of the Holocaust in Poland and Germany. It seeks to highlight the value of a microhistorical approach towards post-Holocaust migrations, as well as the need for a deeper understanding of the different group identities of Jewish migrants. The article adopts a comparative per-spective, examining the experiences of the Cyngel family alongside those of other Jewish survivors from their hometown in Poland. Attentive to the agency of Jewish migrants in re-sponding to the challenges of their post-war situation, the article pursues a history from below of the different displaced persons camps through which the Cyngels passed, comple-mented by a historiographic analysis drawing above all on camp administrations archives, alongside archival collections located in Poland and those of diverse international institu-tions. In addition, the article revisits established opinions on different aspects of post-Holo-caust Jewish migration, such as the experiences that shaped the trajectories of migrants and the strategies which they adopted in response to the various constraints imposed on them by the International Refugee Organization (IRO).

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.846
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0140.002

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 head0.070
GPT teacher head0.458
Teacher spread0.387 · 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; both teacher heads agree on what is shown here.

Study designOther design
Domainnot available
GenreMethods

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
Published2020
Admission routes1
Has abstractyes

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