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Record W4321454832 · doi:10.4337/9781800885325.00029

Indian federalism: centralism amidst diversity

2023· book-chapter· en· W4321454832 on OpenAlexfundno aff
Louise Tillin

Bibliographic record

VenueEdward Elgar Publishing eBooks · 2023
Typebook-chapter
Languageen
FieldSocial Sciences
TopicSouth Asian Studies and Conflicts
Canadian institutionsnot available
FundersUniversity of OxfordQueen's UniversityMcGill University
KeywordsFederalismDiversity (politics)ConstitutionCentralized governmentDemocracyDual federalismPolitical sciencePopulationCooperative federalismPublic administrationGeographySociologyLawPolitics

Abstract

fetched live from OpenAlex

India is the world's most populous federal system. If roughly 40% of the world's population live in a federal system, almost one in two of them live in India. This chapter introduces the unique model of federalism adopted by India in its 1950 constitution. India's flexible and adaptable form of federalism has enabled innovative approaches to the accommodation of diversity, without which it is unlikely India would have held together as a country or consolidated as a democracy. However, it also points to the ways in which centralizing aspects of India's federal model have been critiqued for enabling central over-reach. The chapter provides suggestions as to how India can be used as a case study running throughout a course on federalism, as well as providing resources on the multiple dimensions of its federal system to enable a more comprehensive single session.

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 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 categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.686
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0040.001
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.058
GPT teacher head0.263
Teacher spread0.205 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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
Published2023
Admission routes1
Has abstractyes

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