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Record W2316777931 · doi:10.5509/201184167

Questioning Borders: Social Movements, Political Parties and the Creation of New States in India

2011· article· en· W2316777931 on OpenAlexvenueno aff
Louise Tillin

Bibliographic record

VenuePacific Affairs · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicSouth Asian Studies and Conflicts
Canadian institutionsnot available
Fundersnot available
KeywordsPoliticsSocial movementPolitical sciencePolitical economySociologyLaw

Abstract

fetched live from OpenAlex

As the world's largest multi-ethnic democracy, India has a federal constitution that is well-equipped with administrative devices that offer apparent recognition and measures of self-governance to territorially concentrated ethnic groups. This article analyzes how demands for political autonomy—or statehood—within the federal system have been used as a frame for social movement mobilization. It focuses on the most recent states to have been created in India: Chhattisgarh, Jharkhand and Uttarakhand, which came into being in 2000. These are the first states to have been created in India on a non-linguistic basis. Their creation has triggered questions about whether the creation of more, smaller states can improve political representation and help to make the state more responsive to diverse needs in India. This article draws attention to the processes which have brought borders into question, drawing social movements and political parties into alignment about the idea of creating new states. It ultimately looks at why the creation of states as a result of such processes may not lead to more substantive forms of political and economic citizenship on the part of marginalized communities. While the focus of the analysis will be on the processes that led up to statehood, the conclusions offer some insights into why pro-poor policy shifts at the national level in India have uneven regional effects. Despite the change in national political regime in India with the election of the Congress-led United Progressive Alliance in 2004, marginalized groups in India continue to experience the state through the refractive lens of multiple regional political histories.

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)0.003
metaresearch head score (Gemma)0.005
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 score0.012
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0100.026
Scholarly communication0.0120.005
Open science0.0010.011
Research integrity0.0020.003
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 head0.026
GPT teacher head0.289
Teacher spread0.263 · 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

Citations17
Published2011
Admission routes1
Has abstractyes

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