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Record W4241286680 · doi:10.24908/iqurcp.7926

On the Rationality of Choice

2017· article· en· W4241286680 on OpenAlexvenueno aff
Thomas E. Simmons

Bibliographic record

VenueInquiry Queen s Undergraduate Research Conference Proceedings · 2017
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Theory and Institutions
Canadian institutionsnot available
Fundersnot available
KeywordsRationalityIrrational numberEcological rationalityDivergence (linguistics)EpistemologyCornerstoneValue (mathematics)Great Rationality DebatePresentation (obstetrics)PsychologyComputer sciencePhilosophyMathematicsMedicine

Abstract

fetched live from OpenAlex

This presentation aims to explore the ubiquity of rationality in how people make choices. Historically, rationality has been conceived of as a scheme of certain values and beliefs, most often those that are compatible with a 'scientific way of thinking'. Subsequently, those who hold a different set of beliefs and values are deemed 'irrational' or considered irreconcilably dissimilar from those who are 'rational.' What typical follows for the 'irrational' are unfavorable labels such as 'dogmatic', 'primitive', or even 'insane'. This presentation rejects these common views and offers an alternate model of rationality that depicts rationality as a template rather than a scheme of values. Rather than emphasize certain values as 'rational', this model emphasizes the role of value itself as the cornerstone of rationality. An advantage of this model is that the both the commonly considered 'rational' and 'irrational' are seen to be employing the same underlying structure in making choices; the divergence is in the values themselves and not the way of thinking. What underlies these arguments is an aim to show that human beings are more alike than different, no matter what kind of choices they make

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)0.004
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
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 score0.384
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.252
GPT teacher head0.375
Teacher spread0.123 · 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
Published2017
Admission routes1
Has abstractyes

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