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Record W4224209482 · doi:10.21203/rs.3.rs-1562037/v1

Evolutionary Causal Matrices as Models of Social Stability and/or Change

2022· preprint· en· W4224209482 on OpenAlexaff
Burton Voorhees

Bibliographic record

VenueResearch Square · 2022
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicOpinion Dynamics and Social Influence
Canadian institutionsAthabasca University
Fundersnot available
KeywordsEigenvalues and eigenvectorsStability (learning theory)Mathematical economicsMatrix (chemical analysis)PopulationBinary numberMatrix normMathematicsNorm (philosophy)EconometricsApplied mathematicsComputer scienceEpistemologySociologyPhysicsChemistryPhilosophy

Abstract

fetched live from OpenAlex

Abstract This paper considers evolutionary causal matrices (ECM), which have been proposed as a tool for determination of population distributions of traits in cases in which traits exert mutual influence on each other. In the case of 2x2 ECM a complete mathematical analysis is given including determination of equilibrium distributions and stability. A theorem is proved relating equilibrium stability to ratios of matrix eigenvalues. Several 2x2 ECMs are studied as potential examples of application to questions of norm compliance and binary decisions. 3x3 EMCs are considered as possible examples for modeling political debate between opposed parties with an intermediary group of independents.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.090
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.002
Research integrity0.0000.001
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 head0.148
GPT teacher head0.435
Teacher spread0.287 · 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 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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