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Record W2775828104 · doi:10.1017/s1479244317000579

TRANSLATED LIBERTIES: KARSANDAS MULJI'S<i>TRAVELS IN ENGLAND</i>AND THE ANTHROPOLOGY OF THE VICTORIAN SELF

2017· article· en· W2775828104 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueModern Intellectual History · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicIndian History and Philosophy
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAmateurContextualizationSubject (documents)EthnographyState (computer science)SociologyHistoryLawAnthropologyPhilosophyPolitical science

Abstract

fetched live from OpenAlex

Through an analysis and historical contextualization of Gujarati writer Karsandas Mulji's Travels in England (1866), this article makes two interrelated arguments. First, Indian liberals' efforts to translate notions of liberty exposed the gap between liberalism's subtractive and additive projects, its abolition of customary constraints on the subject and its imposition of new constraints. Second, Mulji's travelogue suggests the complexity of anthropology in post-1850s India, when an amateur form of social science persisted alongside the emergence of the ethnographic state. As an amateur ethnologist, Mulji drew freely on source material from Henry Mayhew to Samuel Smiles to present England as a moral template for India. His turn to self-help or self-improvement literature, moreover, suggests the global scope of a mid-Victorian ethical culture that set the stage for the ethical concerns of anticolonial thinkers like M. K. Gandhi.

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.

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Not applicablehigh
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Qualitativemedium
models splitAgreement compares identical category sets and study designs across arms.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.996
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.004
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.032
GPT teacher head0.210
Teacher spread0.178 · 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