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Record W4213290014 · doi:10.1017/s0026749x21000573

Constructing a caste in the past: Revisionist histories and competitive authority in South India

2022· article· en· W4213290014 on OpenAlexfundno aff
Tori Gross

Bibliographic record

VenueModern Asian Studies · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicSouth Asian Cinema and Culture
Canadian institutionsnot available
FundersFulbright AssociationSocial Sciences and Humanities Research Council of CanadaWenner-Gren Foundation
KeywordsCasteCivilityPoliticsAgrarian societyTamilAppealHonourPolitical scienceOpposition (politics)ColonialismPolitical economySociologyGenealogyGender studiesHistoryEthnologyLaw

Abstract

fetched live from OpenAlex

Abstract This article examines the recent political history of the Devendrakula Vellalars (henceforth, Devendras). Officially recognized by the state and union governments in 2020 and 2021, this novel consolidated caste formation includes a broad range of formerly endogamous ‘Untouchable’ communities spread throughout Tamil Nadu but most highly concentrated in its southern half. I argue that the communities constituting the Devendras have been socio-economically diverse for at least the past century and thus do not necessarily share the same political priorities. They have, nonetheless, attempted to unite in opposition to the politically powerful Thevars (Other Backward Class or OBC) who are themselves a consolidated caste formation that grew out of colonial domination. The Devendras's economic diversity has, however, troubled their oppositional political consolidation, compelling the production of revisionist mythico-histories that appeal to widely held desires for authority and honour. Disavowing the Dalit past and recasting the Devendras as the descendants of heroes, such mythico-histories produce a collective identity characterized by the ideals of righteous self-sacrifice, valour, and agrarian civility. Devendras's identarian claims are, however, reliant on the acceptance of internal and external audiences, some of which violently oppose their assertions. They nevertheless seek recognition, and in so doing empower themselves by gathering strength in numbers.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.083

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.003
Science and technology studies0.0200.028
Scholarly communication0.0120.003
Open science0.0020.006
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0030.000

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 head0.039
GPT teacher head0.254
Teacher spread0.214 · 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 designQualitative
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

Citations11
Published2022
Admission routes1
Has abstractyes

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