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Record W2255005615 · doi:10.1177/2167702615622204

Unmasking One’s True Self Facilitates Positive Relational Outcomes

2016· article· en· W2255005615 on OpenAlexaff
M. Leili Plasencia, Charles T. Taylor, Lynn E. Alden

Bibliographic record

VenueClinical Psychological Science · 2016
Typearticle
Languageen
FieldPsychology
TopicAnxiety, Depression, Psychometrics, Treatment, Cognitive Processes
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPsychologySocial anxietySocial cognitionCognitionSocial psychologyAnxietyDevelopmental psychologyCognitive psychology

Abstract

fetched live from OpenAlex

Individuals with social anxiety disorder (SAD) are motivated to conceal what they perceive to be personal inadequacies. They recognize, however, that their behavior does not convey who they genuinely are. Here, we examined whether increasing perceived authenticity facilitates positive social functioning in these individuals. Participants diagnosed with SAD ( N = 72) engaged in two social interactions with experimental confederates. Prior to the second interaction, participants were randomly assigned to one of two conditions equated on all elements except a safety behavior reduction procedure intended to increase self-authenticity. As hypothesized, increased authenticity led to beneficial changes in the cognitive, affective, and motivation processes that promote relational functioning. These results suggest that the experience of expressing one’s authentic self may reduce SAD-related social impairment.

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)0.000
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.200
GPT teacher head0.494
Teacher spread0.294 · 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

Citations48
Published2016
Admission routes1
Has abstractyes

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