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Record W2890990552 · doi:10.3386/w18288

International Trade and Institutional Change: Medieval Venice's Response to Globalization

2012· preprint· en· W2890990552 on OpenAlexafffund
Diego Puga, Daniel Trefler

Bibliographic record

VenueNational Bureau of Economic Research · 2012
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicHistorical Economic and Social Studies
Canadian institutionsSocial Sciences and Humanities Research CouncilUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of CanadaEuropean CommissionComunidad de Madrid
KeywordsOpenness to experiencePoliticsMonopolizationParliamentCompetition (biology)Context (archaeology)Dominance (genetics)InequalityGlobalizationPolitical sciencePolitical economyEconomyEconomicsGeographyMarket economyLawMonopoly

Abstract

fetched live from OpenAlex

International trade can have profound effects on domestic institutions. We examine this proposition in the context of medieval Venice circa 800-1350. We show that (initially exogenous) increases in long-distance trade enriched a large group of merchants and these merchants used their new-found muscle to push for constraints on the executive i.e., for the end of a de facto hereditary Doge in 1032 and for the establishment of a parliament or Great Council in 1172. The merchants also pushed for remarkably modern innovations in contracting institutions (such as the colleganza) that facilitated large-scale mobilization of capital for risky long-distance trade. Over time, a group of extraordinarily rich merchants emerged and in the almost four decades following 1297 they used their resources to block political and economic competition. In particular, they made parliamentary participation hereditary and erected barriers to participation in the most lucrative aspects of long-distance trade. We document this 'oligarchization' using a unique database on the names of 8,103 parliamentarians and their families' use of the colleganza. In short, long-distance trade first encouraged and then discouraged institutional dynamism and these changes operated via the impacts of trade on the distribution of wealth and power.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.856
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.370
GPT teacher head0.454
Teacher spread0.084 · 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 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

Citations12
Published2012
Admission routes2
Has abstractyes

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