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Record W3022570013 · doi:10.3386/w23208

The Historical State, Local Collective Action, and Economic Development in Vietnam

2017· preprint· en· W3022570013 on OpenAlexafffund
Melissa Dell, Nathaniel Lane, Pablo Querubín

Bibliographic record

VenueNational Bureau of Economic Research · 2017
Typepreprint
Languageen
FieldSocial Sciences
TopicCulture, Economy, and Development Studies
Canadian institutionsCanadian Institute for Advanced Research
FundersWeatherhead Center for International Affairs, Harvard UniversityCanadian Institute for Advanced ResearchYale University
KeywordsCollective actionState (computer science)Action (physics)Economic geographyPolitical scienceGeographyComputer sciencePhysicsLawPolitics

Abstract

fetched live from OpenAlex

This study examines how the historical state conditions long-run development, using Vietnam as a laboratory.Northern Vietnam (Dai Viet) was ruled by a strong centralized state in which the village was the fundamental administrative unit.Southern Vietnam was a peripheral tributary of the Khmer (Cambodian) Empire, which followed a patron-client model with weaker, more personalized power relations and no village intermediation.Using a regression discontinuity design across the Dai Viet-Khmer boundary, the study shows that areas historically under a strong state have higher living standards today and better economic outcomes over the past 150 years.Rich historical data document that in villages with a strong historical state, citizens have been better able to organize for public goods and redistribution through civil society and local government.This suggests that the strong historical state crowded in village-level collective action and that these norms persisted long after the original state disappeared.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.072
Threshold uncertainty score0.144

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 studies0.0010.002
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.347
GPT teacher head0.504
Teacher spread0.157 · 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

Citations21
Published2017
Admission routes2
Has abstractyes

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