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Record W3193761997 · doi:10.26443/jiows.v5i1.101

The Reparation Debate after the Abolition of Indenture

2021· article· en· W3193761997 on OpenAlexaffvenue
Heena Mistry

Bibliographic record

VenueThe Journal of Indian Ocean World Studies · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicColonial History and Postcolonial Studies
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsRepatriationDiasporaColonialismContext (archaeology)NegotiationPolitical scienceState (computer science)NationalismPolitical economyGender studiesHistoryLawSociology

Abstract

fetched live from OpenAlex

While campaigning for the abolition of indenture, Indian elites encouraged indentured Indians and their descendants to repatriate to India to contain the dispersion of Indian unskilled labourers. After the abolition of indenture in 1917, the repatriation of ex-indentured communities became a source of contention between Indians globally, as many repatriates faced marginalization and ostracization within India. Some, such as M.K. Gandhi and Charles Freer Andrews, revised their position from promoting repatriation as a strategy for containing the tragedies of indenture, to arguing that Indian national liberation from empire would better position an independent Indian state to negotiate on behalf of Indians abroad. Others, such as ocean-crossing activist, Bhawani Dayal Sannyasi, and journalist, Benarsidas Chaturvedi, argued that blanket calls for repatriation ignored the needs of repatriates and left Indians in British colonies who chose not to make a life in India at the height of the Indian anticolonial nationalist movement. These diverse and conflicting perspectives surrounding repatriation shed light on the global Indian diaspora in the context of late colonial India.

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)0.029
metaresearch head score (Gemma)0.032
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.029
Threshold uncertainty score0.153

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0290.032
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0230.049
Scholarly communication0.0180.014
Open science0.0030.008
Research integrity0.0180.022
Insufficient payload (model declined to judge)0.0040.001

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 head0.021
GPT teacher head0.326
Teacher spread0.305 · 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 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

Citations0
Published2021
Admission routes2
Has abstractyes

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