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Record W3122781686

Microfinance and the Decline of Poverty: Evidence from the Nineteenth-Century Netherlands

2013· preprint· en· W3122781686 on OpenAlexaboutno aff
Heidi Deneweth, Oscar Gelderblom, Joost Jonker

Bibliographic record

VenueData Archiving and Networked Services (DANS) · 2013
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicHistorical Economic and Social Studies
Canadian institutionsnot available
FundersIllinois-Indiana Sea Grant, University of IllinoisErasmus Universiteit RotterdamUniversity of CambridgeYale University
KeywordsMicrofinanceFinancial intermediaryPovertyEconomic interventionismPosition (finance)Poor peopleLoanQuarter (Canadian coin)Financial systemFinancial marketGovernment (linguistics)EconomicsBusinessFinanceEconomic growthPolitical sciencePoliticsGeography
DOInot available

Abstract

fetched live from OpenAlex

Applying insights from recent literature on the financial behaviour of poor households in developing countries to the nineteenth-century Netherlands, we show that micro finance type institutions failed to alleviate the country¡¯s persistent poverty for the same reasons found today. The numerous institutions launched failed to reach the customers targeted because, like the poor households analyzed in the modern literature, the Dutch poor lacked the money to use them and relied on a combination of makeshift and network solutions instead until rising wages from about 1870 widened their options. Consequently growth preceded finance, not the other way around.

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)0.006
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.257
Threshold uncertainty score0.512

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.040
GPT teacher head0.231
Teacher spread0.190 · 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

Citations0
Published2013
Admission routes1
Has abstractyes

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