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Record W2944611778 · doi:10.3390/rel10050313

Coming Home (Ghar Wapsi) and Going Away: Politics and the Mass Conversion Controversy in India

2019· article· en· W2944611778 on OpenAlexaff
Yashasvini Rajeshwar, Roy C. Amore

Bibliographic record

VenueReligions · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicIndian History and Philosophy
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsHinduismCastePoliticsReligious studiesPolitical scienceSociologyLawHistoryPhilosophy

Abstract

fetched live from OpenAlex

This article addresses two recent socio-religious trends in India: mass conversions to Hinduism (Ghar Wapsi) and mass conversions from Hinduism. Despite officially being a secular nation, organizations allied with the ruling Bharatiya Janata Party (BJP) are actively promoting mass conversions to Hinduism. Other religions organize mass conversions, usually of Dalits, away from Hinduism and its legacy of caste discrimination. While several states have controversial laws placing restrictions on mass conversions from Hinduism, mass conversions to Hinduism are often seen as being promoted rather than restricted.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0140.022
Scholarly communication0.0100.003
Open science0.0010.005
Research integrity0.0020.005
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 head0.008
GPT teacher head0.181
Teacher spread0.173 · 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

Citations14
Published2019
Admission routes1
Has abstractyes

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