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Record W2460745778 · doi:10.1177/0021909616653258

Social Movements and State Repression in India

2016· article· en· W2460745778 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Asian and African Studies · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicSouth Asian Studies and Conflicts
Canadian institutionsYork University
Fundersnot available
KeywordsState (computer science)Political economyMovement (music)Social movementIdeologyDemocracyPoliticsPolitical scienceSociologyCriminologyDevelopment economicsLawEconomics

Abstract

fetched live from OpenAlex

State repression is particularly likely when social movements target property relations that cause ordinary citizens to suffer. Whether these movements are violent, and whether the state is a liberal democracy is a contingent matter. This is illustrated by India’s ‘Maoist movement’ (which is also known as the Naxalite movement because it originated in an area called Naxalbari, located in India’s West Bengal State). Where necessary, sections of this movement use violent methods to fight for justice for aboriginal peoples and peasants. This strategy, which the author, incidentally, does not endorse, has been seen by the state as the greatest internal military threat to it. Such a perception invites state violence. What is often under-emphasized or ignored is that the movement is an economic, political and ideological threat, and not just a military threat, and it is so through its localized alternative developmental activities, and this is also a reason for the state’s violent response to it.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.442
Threshold uncertainty score0.226

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.034
GPT teacher head0.339
Teacher spread0.304 · 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