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Record W2271280593 · doi:10.1111/roiw.12061

Social Capital, Network Effects, and Savings in Rural <scp>V</scp>ietnam

2014· article· en· W2271280593 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

VenueReview of Income and Wealth · 2014
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMicrofinance and Financial Inclusion
Canadian institutionsTrinity College
FundersUnited Nations University World Institute for Development Economics Research
KeywordsGrassrootsSocial capitalQuality (philosophy)Capital (architecture)EconomicsBusinessPublic economicsMicroeconomics

Abstract

fetched live from OpenAlex

Information failures are a major barrier to formal financial saving in low‐income countries. We explore the extent to which social capital in rural V ietnam plays a role in increasing formal savings where knowledge gaps exist. Social capital is defined as information sharing and the elimination of information asymmetries through active participation in the Women's Union. We consider high‐ and low‐quality networks in terms of the quality of information transmitted. We find that membership of high‐quality networks leads to higher levels of saving in formal financial institutions and saving for productive investments. Our results support a role for social capital in facilitating savings and suggest that transmitting financial information through the branches of the Women's Union could be effective in increasing formal savings at grassroots level. We also conclude that it is important to ensure that the information disseminated is accurate given that behavioral effects are also found in networks with low‐quality information.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.364
Threshold uncertainty score0.618

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.008
GPT teacher head0.233
Teacher spread0.225 · 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