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Record W4404226511 · doi:10.31857/s0130386424010057

“Les Miserables” Children of Great Britain in Canada: Maria Rye’s Migration Programme

2024· article· en· W4404226511 on OpenAlexaboutno aff
Olga V. Yablonskaya

Bibliographic record

VenueNovaia i noveishaia istoriia · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsGeographyPolitical science

Abstract

fetched live from OpenAlex

In this paper, the author explores Maria Susan Rye’s emigration society. She initiated the relocation of British children from workhouses and orphanages to Canada in 1869. Documentary and narrative sources have rarely been used to explore this “inconvenient” topic of British history. Few works by Western researchers of child migration appeared only at the end of the twentieth century. In the article, the author analyses controversial events in the history of Great Britain and Canada in the nineteenth century. The purpose of the work is to consider the reasons for resettlement, Rye’s migration plan, the attitude of the British public towards it, its practical implementation in the Dominion, and the living conditions of minors in Canada. The author notes that the pauperisation of the British population was a major factor in the juvenile emigration in the context of industrialisation and demographic growth of the cities. Rye’s plan was to take children from slums and place them in Canadian families. The author pays special attention to Andrew Doyle’s mission. He was commissioned by the British government to investigate the activities of Rye, her colleagues, and the living conditions of the migrants. The author demonstrates that Doyle exaggerated the abuse and lack of supervision of children in order to discredit Rye’s project and impose the workhouse system on Canada. She concludes that the informal control of migrants practised by Rye should have been supplemented by legislative protection of the rights and interests of British minors in Canada.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.486
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.017
GPT teacher head0.229
Teacher spread0.213 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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