MétaCan
Menu
Back to cohort
Record W2413078620

Appropriation in Guise of Tolerance: Neo-Hinduism and its Reception of the 'Other'

2013· article· en· W2413078620 on OpenAlexaff
Avishek Ray

Bibliographic record

VenueSSRN Electronic Journal · 2013
Typearticle
Languageen
FieldArts and Humanities
TopicIndian History and Philosophy
Canadian institutionsTrent University
Fundersnot available
KeywordsHinduismIntelligentsiaAppropriationPoliticsAestheticsSociologySecularismIdentity (music)EpistemologyPhilosophyReligious studiesLawPolitical science
DOInot available

Abstract

fetched live from OpenAlex

Hinduism, in the writings of Indian (Hindu) intelligentsia in the nineteenth century and beyond, right from Radhakrishnan to Amartya Sen, has been eulogistically portrayed as very tolerant and receptive of other religions-cultures. No knowledge is ever neutral; rather it serves the purpose of those who produce it. This article, therefore, re-examines these (often hyperbolic) claims and the underlying motivations involved therein. This is not however to say Hinduism is/was intolerant. But the objective of the paper is to scrutinize the politics of the truth claim in saying that Hinduism is tolerant and the nature of identity politics inherent therein. The article demonstrates ‘how one [read: the ‘modern-secular’ Indian] construes oneself in the present expresses the continuity between how one construes oneself as one was in the past and how one construes oneself as one aspires to be in the future’. (Weinreich & Saunderson, 2004: 120) It points to how in the collective memory (of the ‘secular’ Indian) Hinduism has always been construed, needless to say anachronistically, in tandem with the idea of 'India' which is barely a few decades old. The article reveals how this politics of remembering oneself within the discursive legacy of purported ‘tolerance’ actually dismembers certain ethnic groups from one’s cultural past.

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)0.005
metaresearch head score (Gemma)0.006
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 score0.014
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0100.067
Scholarly communication0.0140.008
Open science0.0020.007
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 head0.012
GPT teacher head0.187
Teacher spread0.175 · 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

Citations0
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueSSRN Electronic JournalSame topicIndian History and PhilosophyFrench-language works237,207