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Record W2768026585 · doi:10.5539/ijps.v9n4p44

Posture and Social Problem Solving, Self-Esteem, and Optimism

2017· article· en· W2768026585 on OpenAlexvenueno aff
Sarah Nielsen

Bibliographic record

VenueInternational Journal of Psychological Studies · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Intergroup Psychology
Canadian institutionsnot available
Fundersnot available
KeywordsOptimismPsychologyExpansiveFeelingSocial psychologyEmpowermentTask (project management)Self-esteemPower (physics)Self-efficacySelf-confidenceExpansive clayDevelopmental psychology

Abstract

fetched live from OpenAlex

When feeling powerful humans and other animals display expansive postures, but can posing in expansive and powerful postures also generate empowerment? Researchers have studied the “power posing effect” the concept that powerful expansive postures generate empowerment, and found conflicting evidence. Some evidence of power posing’s impact shows increased hormones and a variety of behaviors indicating greater confidence. Yet still others have found no effect on hormones or behaviors, and suggest the impact of power posing is overstated. The goal of this project was to replicate and extend previous knowledge and contribute to the debate as to the efficacy of power posing, specifically examining the impact on participants’ self-reported social problem-solving efficacy, self-esteem, and optimism. 119 participants were randomly assigned to one of three conditions: high power pose, low power pose, or a control group with a puzzle solving task, and asked to complete self-report measures of optimism, self-esteem, and problem-solving self-efficacy. Current findings suggest expansive posture demonstrates no measurable impact on psychological attitudes, and contributes to recent literature contradicting the power posing effect. Research and practical implications are discussed.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.551
Threshold uncertainty score0.730

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 studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.098
GPT teacher head0.470
Teacher spread0.372 · 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.

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

Citations3
Published2017
Admission routes1
Has abstractyes

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