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Record W2781873943 · doi:10.31142/ijtsrd7163

Economic Impact of MGNREGA Workers in Thiruvananthapuram District

2017· article· en· W2781873943 on OpenAlexaff
N. Seetha Lekshmi, R. Rathiha

Bibliographic record

VenueInternational Journal of Trend in Scientific Research and Development · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Economics and Practices
Canadian institutionsImpact
Fundersnot available
KeywordsBusiness

Abstract

fetched live from OpenAlex

MGNREGA is an ambitious scheme providing employment to rural people of India. The basic aim of Mahatma Gandhi National Rural Employment Guarantee Act is to enhance livelihood security of household in rural area. By this scheme Govt. gives assurance of employment to unskilled rural laborer for 100 days. With better implementation such type of scheme may be an effective weapon to fight against poverty. It also aims at transforming the rural areas by improving the economic conditions of people. Rural economy is the back Indian economic development. Providing employment to rural households will certainly boost the economy. It increases demand for goods and services. In this article an effort has been made to analyses the economic impact of MGNREGA scheme on the life of beneficiaries of Thiruvanthapuram district. The findings of the study revealed that the programme has brought the change in the lives of the beneficiaries. Though it is always a debatable issue that such changes, by MGNREGA are sustainable or temporary.

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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.201
Threshold uncertainty score0.652

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 communication0.0010.001
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 head0.119
GPT teacher head0.403
Teacher spread0.284 · 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 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

Citations1
Published2017
Admission routes1
Has abstractyes

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