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On Austrian Refugee Children: Agency, Experience, and Knowledge in Ernst Papanek's “Preliminary Study” from 1943

2020· article· en· W4234003194 on OpenAlexaff
Swen Steinberg

Bibliographic record

VenueJournal of Austrian-American History · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicEuropean history and politics
Canadian institutionsCarleton University
Fundersnot available
KeywordsRefugeeAgency (philosophy)PersecutionExperiential learningSociologyNazismGender studiesPolitical scienceCriminologyPsychologyPedagogySocial scienceLawPolitics

Abstract

fetched live from OpenAlex

Abstract In 1943 Viennese refugee pedagogue Ernst Papanek turned in his master's thesis, “On Refugee Children: A Preliminary Study,” for the New York School of Social Work at Columbia University. Particularly interested in their role in processes of knowledge translation and transfers, he circulated questionnaires among refugee children he had rescued from France to the United States. Through his thesis he gave the children a voice and depicted their agency. This article contextualizes Papanek's approach to the relief efforts in the United States in the early 1940s. Focusing especially on the responses of Austrian refugee children in the questionnaires, it uncovers aspects of the young people's experiential knowledge and how they were further explored in a follow-up study on Papanek's research from 1947. The article draws on recent approaches in migration studies that look at the intersection of knowledge and the experiences of young migrants, underlining its potential in research for unaccompanied minors and young refugees from Nazi persecution.

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 imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0160.015
Scholarly communication0.0060.005
Open science0.0010.010
Research integrity0.0020.008
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.053
GPT teacher head0.312
Teacher spread0.259 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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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Same venueJournal of Austrian-American HistorySame topicEuropean history and politicsFrench-language works237,207