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Record W4396662255 · doi:10.4236/me.2024.154022

A Kinetics-Based Approach to Production: Theory and Evidence

2024· article· en· W4396662255 on OpenAlexaff
Bernard C. Beaudreau

Bibliographic record

VenueModern Economy · 2024
Typearticle
Languageen
FieldEnergy
TopicGlobal Energy and Sustainability Research
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsProduction (economics)EconomicsKineticsProduction theoryMathematical economicsEconometricsComputer scienceMicroeconomicsPhysicsClassical mechanics

Abstract

fetched live from OpenAlex

Production theory has, over the course of the past two centuries, been besieged by criticism, ranging from its weak fundamentals to its lack of coherence with the physical sciences. Yet, no real alternatives have emerged with the result that neoclassical production theory continues to hold sway much as it did over the past century. This paper presents a consilient theory of production, one that is grounded in classical mechanics, is empirically validated, and sheds light on myriad productivity-related phenomena. Specifically, a two-tiered approach to modeling production is proposed. In the first tier, a kinetics-based theory is developed where output is an increasing function of energy consumption, in keeping with basic physics. In the second tier, the organization of energy-based material processes (the first tier) is modeled. The resulting model is estimated using U.S. manufacturing two-digit SIC data from 1947 to 1989.

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)0.005
metaresearch head score (Gemma)0.018
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 score0.013
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.018
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0050.006
Science and technology studies0.0010.011
Scholarly communication0.0060.013
Open science0.0040.002
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0130.003

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 head0.030
GPT teacher head0.279
Teacher spread0.250 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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