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Record W2757740123 · doi:10.1111/aswp.12129

The impact of the hope growing account program on participants’ economic well‐being in South Korea

2017· article· en· W2757740123 on OpenAlexaff
Soyoon Weon, David W. Rothwell

Bibliographic record

VenueAsian Social Work and Policy Review · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicPoverty, Education, and Child Welfare
Canadian institutionsMcGill University
Fundersnot available
KeywordsEconomicsDemographic economicsHousehold incomeGovernment (linguistics)Low incomeEstimationIncome SupportNet national incomeComprehensive incomeAdjusted gross incomeIncome in kindLabour economicsSocioeconomicsEconomic growthPublic economicsBusinessGross incomeGeography

Abstract

fetched live from OpenAlex

In 2010, the Korean government introduced the Hope Growing Account (Hope) program. The Hope program combines elements of a social assistance scheme (monthly income grants) with matched funds for savings to encourage the working poor to increase income and build assets. This longitudinal study estimated changes in household economic well‐being among 895 low‐income households who participated in Hope between 2010 and 2012. Economic well‐being was measured by changes in household monthly income and income‐to‐needs ratio. The adjusted difference‐in‐differences estimation revealed that the impact of Hope varied over household income distributions: lower income households were more likely to increase their monthly earned income and income‐to‐needs ratio compared to demographically similar non‐participants, while higher income households were less likely to increase their income and income‐to‐needs ratio. We describe how future research is needed to better understand how the Hope program impacts household assets and behavioral changes in the long run.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.658
Threshold uncertainty score0.998

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 studies0.0030.000
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 head0.035
GPT teacher head0.380
Teacher spread0.346 · 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.

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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