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Record W3210116853 · doi:10.32920/ryerson.14648979.v1

Naturalistic observation of perfectionistic behaviours

2021· preprint· en· W3210116853 on OpenAlexaff
Hanna McCabe‐Bennett

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPsychology
TopicPerfectionism, Procrastination, Anxiety Studies
Canadian institutionsWilfrid Laurier UniversityToronto Metropolitan University
Fundersnot available
KeywordsPerfectionism (psychology)PsychologyContext (archaeology)PsychopathologyNaturalistic observationClinical psychologySample (material)Developmental psychologySocial psychology

Abstract

fetched live from OpenAlex

Perfectionism plays an important role across psychopathology. However, there are almost no naturalistic studies that examine the function of perfectionistic behaviours in everyday life. The purpose of this study is to examine predictors, contextual triggers, frequency, and outcomes of 10 proposed perfectionistic behaviours across a 14-day monitoring period in a community sample: Overpreparing, repeating behaviours, excessive reassurance seeking, excessive organizing, excessive perseverance, quitting too soon, procrastinating, refusing to delegate, avoiding situations where standards may be threatened, and attempting to change other people’s behaviour. Correlates and predictors of these behaviours and their related features are discussed in the context of previous research that has examined these behaviours in less naturalistic ways. The findings of the present study have implications for future research regarding behavioural manifestations of perfectionism, and may provide clinicians with important information about perfectionistic behaviours. Additionally, findings using new perfectionism measures provide evidence for their utility with nonclinical samples.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.196
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.001
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 head0.052
GPT teacher head0.341
Teacher spread0.288 · 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.

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

Citations4
Published2021
Admission routes1
Has abstractyes

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