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Record W2025454230 · doi:10.1017/s004740450141205x

<scp>Roland J.-L. Breton</scp>, <i>Atlas of the languages and ethnic communities of South Asia</i>. Walnut Creek, London &amp; New Delhi: Altamira Press, 1997. Pp. 231. Hb $65.00.

2001· article· en· W2025454230 on OpenAlexaboutno aff
Harold F. Schiffman

Bibliographic record

VenueLanguage in Society · 2001
Typearticle
Languageen
FieldSocial Sciences
TopicSouth Asian Studies and Conflicts
Canadian institutionsnot available
Fundersnot available
KeywordsIndian subcontinentCensusEthnic groupGeographySri lankaSouth asiaHistoryEthnologySociologyAnthropologyDemographyPopulation

Abstract

fetched live from OpenAlex

This is an English version of the author's French work, Atlas géographique des langues et des ethnies de l'Inde et du Subcontinent , (Les Presses de l'Université Laval, Québec, 1976.) Since it was originally based on data from the 1971 (or even earlier) censuses of India, Nepal, Pakistan, and Sri Lanka (and since Bangladesh was part of Pakistan in 1971, and Bhutan data were not reliable earlier), it has been updated to include data from various regional census sources, mostly those conducted in 1981 and 1991. One notes that there are various censuses of Nepal (1952/54, 1971, 1981, 1991) cited, but that Sri Lanka does not seem to have done one since 1953. The cartographic techniques have also benefited from this updating, with new methods of representation not previously available. This makes it possible to compare various increases of speakers and languages in various parts of the subcontinent, in tables added for this purpose. This version also includes a very useful bibliography of sources – not only various censuses, but also other studies of language distribution, language classification, ethnicity, and language issues. There are also a language classification and plate index, a subject and author index, and material on the diffusion of South Asian languages and scripts outside the subcontinent proper.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.127
Threshold uncertainty score0.936

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.031
GPT teacher head0.305
Teacher spread0.274 · 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.

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
Published2001
Admission routes1
Has abstractyes

Explore more

Same venueLanguage in SocietySame topicSouth Asian Studies and ConflictsFrench-language works237,207