MétaCan
Menu
Back to cohort
Record W2982658132

A Tale of Two Markets and the Role of Prosperous Market-Augmenting Governments

2016· article· en· W2982658132 on OpenAlexvenueno aff
Sanghack Lee

Bibliographic record

VenueReview of Economics and Finance · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic, financial, and policy analysis
Canadian institutionsnot available
Fundersnot available
KeywordsProsperityProperty rightsEnforcementGovernment (linguistics)Market failureEconomicsMarket economyBusinessInternational economicsInternational tradeEconomic growthPolitical scienceMicroeconomicsLaw
DOInot available

Abstract

fetched live from OpenAlex

This paper aims to examine the role of market-augmenting government and the two general conditions for achieving economic prosperity. Markets exist ubiquitously, but the markets in rich countries are substantially different from those in poor countries. In rich countries, the markets are the main source of prosperity and thus are called prosperous markets. For a country to achieve rapid economic growth, the country should obtain gains not only from the mutually advantageous trades, but also from the rights-intensive, property rights-intensive or contract rightsintensive productions. The mutually advantageous trades and individual rights-intensive productions take place both in the government-contrived markets and in the rich countries. The countries having a market-augmenting government coined by Olson (2000) tend to grow most rapidly. A market-augmenting government should not only be ¡®strong¡¯ enough to guarantee secure and well-defined property rights and contract enforcement rights to the people, but also be ¡®inhibited¡¯ so as not to deprive or damage individual rights. The two general conditions to achieve economic prosperity are secure and well-defined individual rights, and the absence of any predation. These conditions are realized in countries with market-augmenting governments and rightsrespecting democracies.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.508
Threshold uncertainty score0.513

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 head0.009
GPT teacher head0.202
Teacher spread0.193 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueReview of Economics and FinanceSame topicEconomic, financial, and policy analysisFrench-language works237,207