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Record W3124362125 · doi:10.3917/redp.306.0115

Are Anarcho-Capitalists Insane? Medieval Icelandic Conflict Institutions in Comparative Perspective

2021· article· fr· W3124362125 on OpenAlexaff
Vincent Geloso, Peter T. Leeson

Bibliographic record

VenueRevue d économie politique · 2021
Typearticle
Languagefr
FieldEconomics, Econometrics and Finance
TopicHistorical Economic and Social Studies
Canadian institutionsThe King's University
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

Les anarcho-capitalistes affirment que les institutions de gouvernance privée pourraient se substituer efficacement au gouvernement, et font souvent référence à l’Islande médiévale, qui était gouvernée par le secteur privé. La pensée conventionnelle considère ceci comme insensé : l’Islande médiévale était pauvre, et toute société riche est dotée d’un gouvernement. Bien que cela soit vrai, au regard des normes modernes toutes les sociétés de l’Europe médiévale étaient pauvres. La question de savoir si le niveau de vie aurait été plus élevé sous un gouvernement en Islande médiévale est une question empirique qui n’a pas été évaluée de manière empirique. Nous proposons cette évaluation en considérant le fait que, contrairement à l’Islande, d’autres territoires de l’Europe médiévale étaient en partie gérées par un gouvernement. Nous utilisons des données historiques sur la stature humaine, les salaires et la croissance démographique pour comparer les niveaux de vie dans les territoires européens médiévaux. Le niveau de vie dans l’Europe médiévale gouvernée par l’État ne semble pas avoir été plus élevé qu’en Islande. Les anarcho-capitalistes, semble-t-il, ne sont pas si insensés.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.106
Threshold uncertainty score0.212

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0030.010
Scholarly communication0.0060.003
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.164
GPT teacher head0.316
Teacher spread0.152 · 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 designObservational
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

Citations16
Published2021
Admission routes1
Has abstractyes

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