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Record W4285589590 · doi:10.1142/s2737436x22500066

Anarchy and Higher Trade Equilibrium: A Study of the Russian Old Believer Monasteries

2022· article· en· W4285589590 on OpenAlexaff
Vladimir Maltsev

Bibliographic record

VenueJournal of Economics Management and Religion · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Economy and Marxism
Canadian institutionsInstitute on Governance
Fundersnot available
KeywordsStateless protocolLeverage (statistics)State (computer science)EconomicsEconomyInternational tradeLawPolitical science

Abstract

fetched live from OpenAlex

This paper argues that anarchic communities may breach the dichotomy of anarchy and low level of trade versus the state and a high level of trade. In particular, some anarchic groups may favourably leverage the very fact of their statelessness and turn it into a competitive advantage, enabling a shift to a higher level of trade. In this vein, integration into the state is undesirable as it deprives the community of this competitive advantage and may move it to a lower trade equilibrium. To prove my hypothesis, I provide an account of the contemporary Russian old believer monasteries, located deep in the Siberian taiga. These monasteries continue to remain anarchic well into the 21st century, as their stateless existence gives them a claim to spiritual purity. This enables these monasteries to provide spiritual services to the old believers who are considered religiously impure after integrating into the state. Joining the Russian state would thus deprive the old believer monasteries of their claim to spiritual purity and, by extension, their ability to trade, rendering such action undesirable. As a result, the old believer monasteries remain stateless, while securing a high level of trade with the state-integrated old believers. This is evidenced by the presence of modern equipment, high tech goods, and significant financial resources—items that would be impossible to obtain in the taiga without extensive economic exchange.

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)0.000
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 score0.756
Threshold uncertainty score0.182

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.018
GPT teacher head0.239
Teacher spread0.221 · 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
Published2022
Admission routes1
Has abstractyes

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