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Record W2755139399 · doi:10.1038/s41598-017-12260-3

The role of social status and testosterone in human conspicuous consumption

2017· article· en· W2755139399 on OpenAlexaff
Yin Wu, Christoph Eisenegger, Niro Sivanathan, Molly J. Crockett, Luke Clark

Bibliographic record

VenueScientific Reports · 2017
Typearticle
Languageen
FieldPsychology
TopicEvolutionary Psychology and Human Behavior
Canadian institutionsUniversity of British Columbia
FundersMedical Research CouncilDirectorate for Biological SciencesShenzhen UniversityVienna Science and Technology FundNational Natural Science Foundation of ChinaUniversity of CambridgeWellcome Trust
KeywordsTestosterone (patch)Conspicuous consumptionConsumption (sociology)Data scienceBiologyComputer scienceEndocrinologySociologyBusinessSocial science

Abstract

fetched live from OpenAlex

Conspicuous consumption refers to the phenomenon where individuals purchase goods for signalling social status, rather than for its inherent functional value. This study (n = 166 male participants) investigated how the outcome of a social competition influenced conspicuous consumption, and its association with competition-induced testosterone reactivity. Winning a competition increased both explicit and implicit preferences for higher-status vs. lower-status products, using both natural stimuli (prestigious cars) and laboratory-tagged stimuli of matched value (university T-shirts). Competition also influenced behaviour in an Ultimatum Game, such that winners were more likely to reject unfair offers. Competition outcomes had no discernible influence upon salivary testosterone levels, and neither basal testosterone levels nor testosterone reactivity induced by competition predicted the conspicuous consumption measures. Our data indicate that winning a competition lead to more dominant behaviour, albeit in a manner that is not statistically regulated by testosterone, possibly through increased feeling of entitlement.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score1.000

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 studies0.0020.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.039
GPT teacher head0.362
Teacher spread0.322 · 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 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

Citations17
Published2017
Admission routes1
Has abstractyes

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