<scp>Roland J.-L. Breton</scp>, <i>Atlas of the languages and ethnic communities of South Asia</i>. Walnut Creek, London & New Delhi: Altamira Press, 1997. Pp. 231. Hb $65.00.
Bibliographic record
Abstract
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 machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.300 | 0.207 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".