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Geographical Pattern of Muslim Population in India, 2001

2014· article· en· W2257396199 on OpenAlexvenueno aff
Mehar Singh Gill, Parshotam Dass Bhardwaj, Firuza Begham Mustafa

Bibliographic record

VenueArab world geographer · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Economic Development in India
Canadian institutionsnot available
Fundersnot available
KeywordsPartition (number theory)PopulationHinduismPopulation growthGeographyPovertyIndependence (probability theory)DemographyTotal fertility rateSocioeconomicsDistribution (mathematics)Development economicsEconomic growthSociologyEconomicsResearch methodologyStatisticsFamily planningMathematics

Abstract

fetched live from OpenAlex

The pattern of Muslim population in India reflects the contribution of a number of factors: proselytization, migration, and natural growth rate. The partition of the country in 1947 made its own important contribution, effecting profound changes in the distribution pattern of Muslims that resulted in the migration of about 10 million people to and from the newly created country of Pakistan, but natural growth has been the chief determinant of the growth of India’s Muslim population during the post-independence period. Relatively high growth of the Muslim popu lation in this period is mainly attributable to two factors: a higher incidence of poverty, which is closely correlated with higher fertility; and the persistence of a pro-natal attitude among this population. Higher concentrations of Muslims are found in two types of areas: (a) those that experienced a longer duration of Muslim rule and (b) those located at the margins of the Hindu heartland.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.014
GPT teacher head0.259
Teacher spread0.245 · 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 designObservational
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
Published2014
Admission routes1
Has abstractyes

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