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Geographical Pattern of Muslim Population in India, 2001

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

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
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