MétaCan
Menu
Back to cohort

Impact of Pradhan Mantri Kaushal Vikas Yojana (PMKVY)

2023· article· en· W4318474650 on OpenAlexaboutno aff
Sakshi Malik -

Bibliographic record

VenueInternational Journal For Multidisciplinary Research · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicIndian Economic and Social Development
Canadian institutionsnot available
Fundersnot available
KeywordsCertificateGovernment (linguistics)CertificationDuration (music)Scheme (mathematics)BusinessQuarter (Canadian coin)Demographic economicsLabour economicsEconomic growthMathematicsEconomicsManagementGeography

Abstract

fetched live from OpenAlex

This review paper is about the government of India’s Scheme Pradhan Mantri Kaushal Vikas Yojana (PMKVY), launched in 2015 to encourage and promote skill development in the country by providing free short-duration skill training and incentivizing this by providing monetary rewards to youth for skill certification. People in the programs which are covered under the scheme can avail themselves without having any difficulty. Moreover, all the schemes are scheduled to run in the nearby locality itself. This means there is no need for the additional burden to take by any of the candidates. For learning the basic skills and the courses which will help in their further studies. The certificate provided under the scheme is valid for all kinds of jobs and other programs as an add-on to their service. This certificate is valid for a lifetime and with a limited period. This can be used for various private and public sector jobs and also for nongovernment jobs.

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)0.001
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0170.002

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 head0.242
GPT teacher head0.475
Teacher spread0.233 · 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

Citations4
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal For Multidisciplinary ResearchSame topicIndian Economic and Social DevelopmentFrench-language works237,207