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Record W2104299745 · doi:10.1177/1948550611427772

Sex, “Lies,” and Videotape

2011· article· en· W2104299745 on OpenAlexafffund
Danu Anthony Stinson, Danielle Gaucher, Joanne V. Wood, Lisa B. Reddoch, John G. Holmes, Douglas C. G. Little

Bibliographic record

VenueSocial Psychological and Personality Science · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Intergroup Psychology
Canadian institutionsUniversity of WaterlooUniversity of WinnipegUniversity of Victoria
FundersUniversity of Waterloo
KeywordsPsychologySocial psychologyFemininityImpression formationAgency (philosophy)Test (biology)Impression managementMasculinityCoding (social sciences)Nonverbal communicationSocial perceptionDevelopmental psychologyPerception

Abstract

fetched live from OpenAlex

When presenting themselves to others, people attempt to create the impression that they possess socially desired traits. Verbally claiming to possess such traits is relatively simple, but making good on one’s promises by actually behaving in kind is more challenging. In particular, lower self-esteem individuals’ relational insecurity may undermine their ability to present themselves in a socially desired manner. The present research used a behavioral coding method to test these hypotheses. Participants filmed a brief introductory video in an evaluative, first impression situation. Independent sets of observers then coded participants’ verbal, nonverbal, and global self-presentations on two dimensions: communion/femininity and agency/masculinity. Results revealed that for both sexes, self-esteem was unrelated to participants’ ability to “talk the talk” by verbally describing themselves in a socially valued and gender-role specific manner, but was predictive of participants’ ability to “walk the walk” by actually behaving in kind.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.785
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.009
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.183
GPT teacher head0.414
Teacher spread0.231 · 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; both teacher heads agree on what is shown here.

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

Citations11
Published2011
Admission routes2
Has abstractyes

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