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Record W3199248410 · doi:10.33423/jabe.v23i1.4066

Price Laws and Items of Convenience: An Inquiry Into the Question of “Ancient Middle Class”

2021· article· en· W3199248410 on OpenAlexvenueno aff

Bibliographic record

VenueJournal of Applied Business and Economics · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicAncient Near East History
Canadian institutionsnot available
Fundersnot available
KeywordsEliteClass (philosophy)Middle classConsumption (sociology)Distribution (mathematics)Intervention (counseling)EconomicsLawEconomySociologyPolitical scienceMarket economySocial scienceEpistemologyPsychology

Abstract

fetched live from OpenAlex

The main goal of this study is to make ancient economic data accessible to students and scholars of business and economics. It also demonstrates the capacity of classical and neoclassical economics for making theoretical contributions to economic history and anthropology. Primary data are drawn from Iraq and Iran between the sixth century BCE and the seventh century CE, with comparisons taken from the Mediterranean. Convenience is a useful concept for locating a middle class or an “intermediate economic group” in ancient societies. Symbolically, convenience may be understood through the notion of “item of convenience,” which is necessary for creating an intermediate economic group. Convenience is also associated with comfort, which is only available to the elite and those intermediate economic groups who have access to limited surplus and are engaged in production, distribution, exchange, and consumption. Ancient price laws, which were intended to protect buyers and sellers, testify to institutional intervention among a group of people who were freely engaged in market conduct and desired a more convenient access to fair market prices.

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)0.003
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0030.017
Scholarly communication0.0030.005
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.034
GPT teacher head0.217
Teacher spread0.184 · 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 designNot applicable
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
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Applied Business and EconomicsSame topicAncient Near East HistoryFrench-language works237,207