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Record W2317079875 · doi:10.1037/a0034490

Conceptual and empirical strengths of the authentic/hubristic model of pride.

2014· article· en· W2317079875 on OpenAlexaff
Jessica L. Tracy, Richard W. Robins

Bibliographic record

VenueEmotion · 2014
Typearticle
Languageen
FieldPsychology
TopicEmotions and Moral Behavior
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPrideAttributionConstruct (python library)PsychologySocial psychologyEmpirical researchCognitive psychologyEpistemologyComputer science

Abstract

fetched live from OpenAlex

The authentic/hubristic (A/H) model of pride has been empirically supported by dozens of studies drawing on thousands of participants. The model involves four distinct components, most central of which is the finding that pride is not a unitary construct but rather is comprised of two distinct facets, referred to as authentic and hubristic pride. In the present article, we review the four critical components of the A/H model, and explain why Holbrook and colleagues' (2013) critique raises questions for one part of one of these components only-the attribution distinction between the two prides. We then raise questions for Holbrook and colleagues' alternative model of pride, and conclude by noting several convergences between the two perspectives.

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)0.026
metaresearch head score (Gemma)0.044
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: none
Teacher disagreement score0.026
Threshold uncertainty score0.136

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0260.044
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0030.034
Scholarly communication0.0070.014
Open science0.0030.012
Research integrity0.0040.008
Insufficient payload (model declined to judge)0.0040.000

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 head0.054
GPT teacher head0.344
Teacher spread0.289 · 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

Citations57
Published2014
Admission routes1
Has abstractyes

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