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Record W2792154269 · doi:10.1080/03086534.2018.1431438

‘England Failed to do her Duty towards Them’: The India Office and Pauper Indians in the Metropole, 1857–1914

2018· article· en· W2792154269 on OpenAlexaff
Raminder K. Saini

Bibliographic record

VenueThe Journal of Imperial & Commonwealth History · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicAustralian History and Society
Canadian institutionsMcGill University
Fundersnot available
KeywordsColonialismState (computer science)British EmpireDutyEmpireGovernment (linguistics)LawPoor reliefInstitutionHistorySociologyPolitical scienceEconomic historyPoverty

Abstract

fetched live from OpenAlex

This article examines how the India Office handled cases of destitute Indians, such as sailors and servants, who were stranded in Britain. The empire provided opportunities for work and travel, yet there were no securities for those who were taken advantage of by the system. This article highlights how the India Office was the institution expected to help distressed Indians and yet the secretary of state for India consistently refused to accept official responsibility for them. Nor did the British government try to prevent the problem from occurring in the first place. Instead, the official position taken by the secretary of state for India was to let social institutions intervene, arguing that, as British subjects, Indians could receive relief through the Poor Laws. Workhouses, however, were ill suited to Indians striving to return to their homes. This article addresses these issues through examining three key periods: the early to mid-nineteenth century; a shift in the 1880s when the India Office acknowledged a better policy was needed for the treatment of destitute Indians; and, the turn of the century when a Committee on Distressed Colonial and Indian Subjects was established in 1909. Through a focused study of India Office discourses, this article addresses the ambiguity of imperial policy and assesses how it contributed to competing understandings of British responsibility over imperial subjects.

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)0.009
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 score0.806
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.040
GPT teacher head0.308
Teacher spread0.269 · 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

Citations8
Published2018
Admission routes1
Has abstractyes

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