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Record W4210870037 · doi:10.1002/jhbs.22188

“All emigrants are up to the physical, mental, and moral standards required”: A tale of two child rescue schemes

2022· article· en· W4210870037 on OpenAlexaboutno aff
Wendy Sims‐Schouten, Paul Weindling

Bibliographic record

VenueJournal of the History of the Behavioral Sciences · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical Studies on Reproduction, Gender, Health, and Societal Changes
Canadian institutionsnot available
Fundersnot available
KeywordsEugenicsViewpointsTemporalitySociologyNarrativeIgnoranceIdentity (music)Inclusion (mineral)EmigrationSettlement (finance)Gender studiesPsychologyPolitical scienceLawEpistemologyAesthetics

Abstract

fetched live from OpenAlex

The current paper critically assesses and reflects on the ideals and realities of two major (British) child migration schemes, namely the British Home Child scheme (1869-1930) and the Kindertransport scheme (1938-1940), to add to current understandings of their place within wider international histories of child migration, moral reforms, eugenics, settlement, and identity. Specifically, we focus on constructions of "mentally and physically deficient" children/young people, informed by eugenic viewpoints and biological determinism, and how this guided inclusion and exclusion decisions in both schemes. Both schemes made judgements regarding which children should be included/excluded in the schemes or returned to their country of origin (as was the case with children in the Canadian child migration scheme) fueled by a type of eugenics oriented to transplanting strong physical and psychologically resilient specimens. By viewing the realities of the child migration schemes, including the varied experiences and narratives in relation to child migrants, in light of eugenicist narratives of difference, pathology, victimhood, and contamination, we shed a light on uneven practices, formations of power, and expectations of the times.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.561
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 studies0.0020.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.136
GPT teacher head0.336
Teacher spread0.200 · 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
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

Citations4
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the History of the Behavioral SciencesSame topicHistorical Studies on Reproduction, Gender, Health, and Societal ChangesFrench-language works237,207