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Record W3005435715 · doi:10.1177/1948550619882036

Embodied Capital and Risk-Related Traits, Attitudes, Behaviors, and Outcomes: An Exploratory Examination of Attractiveness, Cognitive Ability, and Physical Ability

2020· article· en· W3005435715 on OpenAlexafffund
Nabhan Refaie, Sandeep Mishra

Bibliographic record

VenueSocial Psychological and Personality Science · 2020
Typearticle
Languageen
FieldPsychology
TopicBehavioral Health and Interventions
Canadian institutionsUniversity of Regina
FundersOntario Problem Gambling Research Centre
KeywordsEmbodied cognitionAttractivenessPsychologyBig Five personality traitsCognitionPersonalitySocial psychologyNeed for cognitionVariance (accounting)Physical attractivenessEconomicsComputer science

Abstract

fetched live from OpenAlex

The relative state model posits two nonindependent pathways to risk. The need-based pathway suggests people take risks when nonrisky options are unlikely to meet their needs. The ability-based pathway suggests people take risks when they possess resources or abilities making them more capable of successfully “pulling off” risk-taking. Growing laboratory and field evidence supports need-based risk-taking. However, little is known about ability-based risk-taking. We examined whether three indicators of embodied capital (attractiveness, cognitive ability, and physical dexterity) were associated with risk-related personality traits, risk-attitudes, behavioral risk-taking, and outcomes associated with risk-taking. Among 328 community members recruited to maximize variance on risk-propensity, we demonstrate that embodied capital indices predict various instantiations of risk-propensity consistent with the relative state model.

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)0.001
metaresearch head score (Gemma)0.005
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.144
GPT teacher head0.448
Teacher spread0.304 · 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

Citations14
Published2020
Admission routes2
Has abstractyes

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