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Record W4412015083 · doi:10.1111/jols.12547

Indigeneity, caste, tribe and the limitations of decolonial thought in South Asian socio‐legal studies: The need for a decolonial–debrahmanical approach

2025· article· en· W4412015083 on OpenAlexaff
Arvind Kumar

Bibliographic record

VenueJournal of Law and Society · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicLaw in Society and Culture
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsCasteTribeSociologyGeographyGender studiesAnthropologyEthnologyPolitical scienceLaw

Abstract

fetched live from OpenAlex

Abstract The dominant decolonial approach in Adivasi studies and South Asian socio‐legal studies is broadly and primarily rooted in a critical study of the British colonial rule, epistemologies, laws and institutions, as they are considered to be the roots of social, cultural, religious, legal and political challenges faced by post‐colonial India. Therefore, in common vocabulary, the decolonial or decolonisation approach is synonymous with identifying and dismantling the legacies of colonial rule and epistemologies. This paper highlights the limitations of the dominant decolonial approach in relation to post‐colonial discourses vis‐à‐vis categories of caste and tribe. I argue that the classification of social groups into caste and tribe has more to do with Brahmanical epistemology than colonial epistemology. Subsequently, drawing upon Adivasi oral narratives from the field, this paper argues that there is a need to look beyond the prevailing decolonial approach and consider a decolonial–debrahmanical approach to address the decolonial challenges in post‐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)0.041
metaresearch head score (Gemma)0.030
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.041
Threshold uncertainty score0.217

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0410.030
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0050.004
Science and technology studies0.0100.084
Scholarly communication0.0170.013
Open science0.0020.012
Research integrity0.0020.005
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 head0.053
GPT teacher head0.344
Teacher spread0.291 · 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 designTheoretical or conceptual
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

Citations3
Published2025
Admission routes1
Has abstractyes

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