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The Sensory Order, Neuroeconomics, and Austrian Economics

2015· reference-entry· en· W2263279483 on OpenAlexaff
William Ν. Butos, Thomas J. McQuade

Bibliographic record

Venuenot available
Typereference-entry
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Theory and Institutions
Canadian institutionsTrinity College
Fundersnot available
KeywordsNeuroeconomicsOrder (exchange)Spontaneous orderRealmEpistemologyPsychologyPositive economicsEconomicsCognitive psychologyPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

In the social science literature spawned by Friedrich Hayek’s “The Sensory Order,” the questions asked were: (1) In what ways does Hayek’s cognitive theory fit with his social theory and with Austrian economics in general? (2) Do we need “The Sensory Order” at all to do our social science, and how does it make a difference in providing insight toward understanding the social realm? This chapter surveys this literature and, by drawing out the ramifications from both Hayek’s work on epistemology and psychology and the ongoing experimental investigations of individual economic behavior, it points to the possibility of a coherent new view of economic and other social systems in which individuals have realistic capabilities, where emergent effects are recognized as macro-phenomena that supervene on micro-activity rather than being simply reducible to it and where systemic characteristics such as adaptation and knowledge generation are given their due.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.664
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.003

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 head0.070
GPT teacher head0.232
Teacher spread0.162 · 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.

Study designNot applicable
Domainnot available
GenreOther

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
Published2015
Admission routes1
Has abstractyes

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