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Linguistic Nationalism in the Telugu-speaking Madras Presidency (1913-1956)

2025· article· en· W4413379238 on OpenAlexaboutno aff
Tiasa Basu Roy

Bibliographic record

VenueInternational Journal For Multidisciplinary Research · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicSouth Asian Studies and Conflicts
Canadian institutionsnot available
Fundersnot available
KeywordsNationalismPresidencySolidarityPoliticsEthnic groupIdentity (music)SociologyAgrarian societyPolitical scienceLinguisticsGender studiesHistoryLawAnthropology

Abstract

fetched live from OpenAlex

Religious nationalism dates back to the sixteenth century, while linguistic nationalism emerged around 1870, reflecting the differing political and economic landscapes of traditional and modern societies. Traditional communities were agrarian and decentralised, while modern societies became centralised and industrialised, enhancing literacy and interaction with institutions. This made language vital for negotiating resources, leading to demands for official recognition of ethnic languages, often opposed by dominant groups. Linguistic nationalism has spurred ethnonational movements in regions like Quebec, Belgium's Flanders and Wallonia, Swiss French and German-speaking areas, and among Dravidian communities in India. Areas organised by language tend to have a stronger sense of identity, as movements for linguistic reorganisation foster solidarity and a common bond among people, reinforcing their shared struggle for identity. This article attempts to understand the formation of Andhra Pradesh, the first linguistic state, after the dissolution of the Madras Presidency.

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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.004
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0000.001
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 head0.169
GPT teacher head0.554
Teacher spread0.385 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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