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Record W2011289147 · doi:10.1537/ase.111.225

Sex Differences in Choices of Tradeoffs between Success and Health

2003· article· en· W2011289147 on OpenAlexaboutno aff
Ryo Oda

Bibliographic record

VenueAnthropological Science · 2003
Typearticle
Languageen
FieldPsychology
TopicEvolutionary Psychology and Human Behavior
Canadian institutionsnot available
Fundersnot available
KeywordsRelocationSalaryPsychologyDemographySelection (genetic algorithm)DaughterSocial psychologyGerontologyMedicineEconomicsSociologyBiology

Abstract

fetched live from OpenAlex

Sexual selection theory and evolutionary psychology predict that males may be more willing than females to discount the future in the pursuit of short-term gains. Wilson et al. (1996) asked university students in Canada to make a choice in hypothetical dilemmas and indicated that males tended to choose their financial success at the cost of their health. In the hypothetical situation, the subject males were willing to be transferred from a small town to a new branch in big city for an increase in salary though the city was famous for its smog and severity of illness was high. This result, however, is not sufficient to prove that males are likely to choose tradeoff between success and health. There are some possibilities that relocation is more acceptable to males than to females. In this study I attempted to replicate Wilson et al.’s results (1996) using Japanese subjects. I also investigated whether the relocation factor affected the choice of males and females differently, using a modified questionnaire that included the hypothetical scenario without any mention of smog or its health effects.

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)0.003
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 score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.150
GPT teacher head0.447
Teacher spread0.298 · 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

Citations1
Published2003
Admission routes1
Has abstractyes

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