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Record W2081566802 · doi:10.1108/03068290010384268

A social contractarian theory of markets: Neoclassicism, Rawls, Gauthier and the alternative

2000· article· en· W2081566802 on OpenAlexaff
Masudul Alam Choudhury

Bibliographic record

VenueInternational Journal of Social Economics · 2000
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Theory and Institutions
Canadian institutionsCape Breton University
Fundersnot available
KeywordsEconomicsSocial contractNeoclassical economicsResource (disambiguation)Resource allocationMicroeconomicsPositive economicsLawManagementPolitical scienceComputer science

Abstract

fetched live from OpenAlex

The study of resource allocation in market venues is taken up in a comparative framework of neoclassical and various social contractarian theories. It is shown that economic theory does not have an explanation of substantive interactions among agents and variables as it does among society, economy and institutions, all of which social contractarian theory necessitates. Thus Rawls’s and Gauthier’s social contractarian theories are examined against neoclassicism and the classical theory of markets and resource allocation. Shortcomings with these theories are pointed out and a purely interactive theory of social contractarianism is propounded. Markets and resource allocation are once again studied in this framework.

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)0.004
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0020.018
Scholarly communication0.0050.009
Open science0.0010.003
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.018
GPT teacher head0.231
Teacher spread0.213 · 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 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

Citations3
Published2000
Admission routes1
Has abstractyes

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