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Record W4402423799 · doi:10.24908/iqurcp18046

The Influence of Social Context on Adolescents’ use of Prototypical Facial Expressions

2024· article· en· W4402423799 on OpenAlexaffvenue
Sarah Shi Hui Wong, Daniel R. Nault

Bibliographic record

VenueInquiry Queen s Undergraduate Research Conference Proceedings · 2024
Typearticle
Languageen
FieldPsychology
TopicEmotional Intelligence and Performance
Canadian institutionsQueen's University
Fundersnot available
KeywordsFacial expressionPsychologyContext (archaeology)Cognitive psychologyDevelopmental psychologySocial psychologyCommunicationHistory

Abstract

fetched live from OpenAlex

Adolescents’ social behaviour varies by social context (e.g., who they are with); they might ‘play it cool’ with peers while displaying vulnerability with caregivers. Yet, the way in which social context affects teenagers’ nonverbal expression is unknown. The current study addresses this knowledge gap by examining how teenagers’ facial expressions differs when discussing emotionally charged topics with a friend vs. with a caregiver. Thirty-one 11 to 16-year-old participants engaged in two separate conversations, with their caregiver and friend, respectively (social context). Within each context, they spoke about emotionally charged topics (happy vs angry) of their choosing (emotional type). Facial analysis software (iMotions) was employed to quantify the prototypicality of angry and happy facial expressions. Two separate within-subject factorial (2x2) ANOVAs were conducted to assess the effect of social context and emotional type on the prototypicality of happy and angry facial expressions. There was a significant main effect of social context on prototypical facial cues of anger (F(1, 30) = 5.45, p = .026) with adolescents exhibiting more prototypical angry expressions with their friends than with their caregivers. Moreover, there was a significant main effect of emotional type on prototypical facial cues of happiness (F(1, 30) = 4.72, p = .038) with adolescents displaying more prototypical happy facial expressions when discussing happy topics compared to angry topics. No other effects were significant. The above main effects were rendered non-significant after accounting for sex assigned at birth and age. As the current study is ongoing, the next steps will be to increase our sample size to boost statistical power and to investigate whether the change in non-verbal encoding we observe across social context relates to teens' socio-emotional functioning. With these results, we can better support teenagers in their emotional expression to foster relationship formation and social success throughout adolescence.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.581
Threshold uncertainty score0.766

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.216
GPT teacher head0.449
Teacher spread0.232 · 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 designTheoretical or conceptual
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

Citations0
Published2024
Admission routes2
Has abstractyes

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