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Record W2772718915 · doi:10.18844/gjhss.v3i1.1731

Building vocational skill training center for unemployed women to eradicate the cycle of poverty in District Nowshera, Pakistan

2017· article· en· W2772718915 on OpenAlexaff
Alina Babar

Bibliographic record

VenueNew Trends and Issues Proceedings on Humanities and Social Sciences · 2017
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicIndian Economic and Social Development
Canadian institutionsAbbott (Canada)
Fundersnot available
KeywordsVocational educationPovertyLivelihoodEconomic growthTraining (meteorology)BusinessSocioeconomicsGeographyEconomicsAgriculture

Abstract

fetched live from OpenAlex

Vulnerable and unemployed women of Nowshera district have no opportunity in their region to create their own employment and sustainable livelihood in order to redeem themselves and their families, out of extreme poverty. Vocational training (VT) is expected to offer skills to uneducated and jobless women there. Vocational training is an essential tool for integrating special people in society and makes them a productive member of community. This paper presents findings of an exploratory study conducted on vocational Center’s of Nowshera district, Khyber Pakhtunkhwa. Keywords: Vocational training, kills development, homeless women, uneducatedhusbands, poverty reduction,rural employment.

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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.697
Threshold uncertainty score0.921

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.085
GPT teacher head0.311
Teacher spread0.226 · 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 designTheoretical or conceptual
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
Published2017
Admission routes1
Has abstractyes

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