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Record W4401717516 · doi:10.1080/13645145.2024.2376742

The itinerant travellee: dubash accounts from eighteenth- and nineteenth-century India

2023· article· en· W4401717516 on OpenAlexaff
Sanjukta Banerjee

Bibliographic record

VenueStudies in Travel Writing · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicColonialism, slavery, and trade
Canadian institutionsYork University
Fundersnot available
KeywordsHinduismColonialismSign (mathematics)HistoryNarrativeHospitalityPower (physics)Reading (process)TourismSociologyLiteratureArtPolitical scienceLawArchaeologyLinguisticsPhilosophy

Abstract

fetched live from OpenAlex

This article seeks to read the travellee in eighteenth- and nineteenth-century travel in India with a focus on the nature of their contemporaneity with the traveller. It questions the overarching explanatory power bestowed on religion in colonial-era European travel accounts through an exploration of the itinerance of the Hindu travellee in early colonial India and the changing functions of the rest house, the latter often mentioned exclusively as a sign of Hindu hospitality in European travel texts of the time. Based on a reading of excerpts from dubash narratives interwoven with details from French and British accounts, the analysis sheds light on travellees as mobile and transitional, their paths intersecting with those of travellers. Travel here emerges as differentiated and constituted by being in place, with instances of shared time marking the experience of movement for all involved.

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)0.001
metaresearch head score (Gemma)0.002
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: Empirical
Teacher disagreement score0.074
Threshold uncertainty score0.147

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0160.012
Scholarly communication0.0070.004
Open science0.0010.006
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0040.000

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 head0.056
GPT teacher head0.366
Teacher spread0.310 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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