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Record W4385446191 · doi:10.1080/14736489.2023.2236462

Intergovernmental relations and the territorial management of ethnic diversity in India

2023· article· en· W4385446191 on OpenAlex
Kham Khan Suan Hausing

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueIndia Review · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicSouth Asian Studies and Conflicts
Canadian institutionsnot available
FundersIndian Council of Social Science Research
KeywordsFederalismPoliticsEthnic groupSociologyDiversity (politics)Political scienceDemisePolitical economyLaw

Abstract

fetched live from OpenAlex

This article examines how and to what extent ethnic diversity underpinned intergovernmental relations (IGR) in deeply divided societies like India. Central to this is the vertical and intermediating roles of political actors, structures and processes of Indian federalism in defining the ways in which ethnic diversity is territorially managed. Unlike Canada or Belgium which have more formal and robust structures of IGR, the inconsequential roles of formal structures of IGR in India unduly leverage centralizing actors, structures and processes in the territorial management of ethnic diversity. Given that these centralizing actors, structures and processes are contingent on political expediency, the dynamic ideas, interests and strategies of centralizing and regionalist actors are particularly salient in defining not only the contours and outcomes of IGRs but also the ways in which “unity in diversity” are negotiated and balanced within the overarching framework of “self-rule and shared rule.”

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)0.001
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 score0.622
Threshold uncertainty score0.153

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.045
GPT teacher head0.330
Teacher spread0.285 · 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