MétaCan
Menu
Back to cohort
Record W2149480820 · doi:10.1093/wber/lhv025

Rural and Urban Migrants in India: 1983–2008

2015· article· en· W2149480820 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe World Bank Economic Review · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Economic Development in India
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsWageDemographic economicsInternal migrationEconomicsGeographyDistribution (mathematics)Sample (material)Rural areaSocioeconomicsSurvey data collectionSurvey samplingLabour economicsDeveloping countryEconomic growthDemographyPopulationPolitical scienceSociologyStatistics

Abstract

fetched live from OpenAlex

This paper characterizes the gross and net migration flows between rural and urban areas in India during the period 1983–2008. Using individual data from the National Sample Survey of India we show that the 5-year gross migration flows constitute about 10% of India's labor force and are stable over time. Migrants tend to be younger and more educated than nonmigrants. They also are more likely to work part-time and in regular employment and less likely to be self-employed. Migrants from rural and urban areas have higher mean and median wages relative to nonmigrants in the same locations. However, there are differences in the size of the wage gaps along the wage distribution and their dynamics over time.

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)0.002
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.496
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.035
GPT teacher head0.296
Teacher spread0.261 · 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