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Record W2149870839 · doi:10.1037/0022-3514.84.6.1303

The interpersonal expression of perfection: Perfectionistic self-presentation and psychological distress.

2003· article· en· W2149870839 on OpenAlexaff
Paul L. Hewitt, Gordon L. Flett, Simon Sherry, Marie Habke, Melanie Parkin, Raymond W. Lam, Bruce McMurtry, Evelyn Ediger, Paul Fairlie, Murray B. Stein

Bibliographic record

VenueJournal of Personality and Social Psychology · 2003
Typearticle
Languageen
FieldPsychology
TopicPerfectionism, Procrastination, Anxiety Studies
Canadian institutionsUniversity of WinnipegYork UniversityUniversity of British Columbia
Fundersnot available
KeywordsPsychologySocial psychologyInterpersonal communicationPerfectionExpression (computer science)DistressPresentation (obstetrics)Context (archaeology)Interpersonal attractionInterpersonal relationshipPersonal distressPromotion (chess)PsychotherapistEmpathy

Abstract

fetched live from OpenAlex

A concept involving the interpersonal expression of perfection, perfectionistic self-presentation, is introduced. It is argued that perfectionistic self-presentation is a maladaptive self-presentational style composed of three facets: perfectionistic self-promotion (i.e., proclaiming and displaying one's perfection), nondisplay of imperfection (i.e., concealing and avoiding behavioral demonstrations of one's imperfection), and nondisclosure of imperfection (i.e., evading and avoiding verbal admissions of one's imperfection). Several studies involving diverse samples demonstrate that perfectionistic self-presentation is a valid and reliable construct and a consistent factor in personal and interpersonal psychological distress. It is argued that the need to promote one's perfection or the desire to conceal one's imperfection involves self-esteem regulation in the interpersonal context.

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)0.001
metaresearch head score (Gemma)0.006
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.048
GPT teacher head0.379
Teacher spread0.331 · 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

Citations497
Published2003
Admission routes1
Has abstractyes

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Same venueJournal of Personality and Social PsychologySame topicPerfectionism, Procrastination, Anxiety StudiesFrench-language works237,207