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Record W4285008741 · doi:10.1037/apl0001028

Toward a holistic perspective of congruence research with the polynomial regression model.

2022· article· en· W4285008741 on OpenAlexaff
Yongheng Yao, Zhenzhong Ma

Bibliographic record

VenueJournal of Applied Psychology · 2022
Typearticle
Languageen
FieldPsychology
TopicFamilies in Therapy and Culture
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsCongruence (geometry)PsycINFOPsychologySocial psychologyMEDLINEPolitical science

Abstract

fetched live from OpenAlex

. We find that congruence researchers often fail to consider all the conditions required to test congruence effects. Our reanalysis of these studies shows that when all required conditions are used, the exact correspondence effect, sometimes also labeled as the exact match effect or the perfect match effect, is only supported in three studies. Caution is hence warranted both for citing these studies as evidence of congruence and for proposing practical implications based on the findings in these studies. A holistic perspective is then proposed in this study to facilitate the proper application of the PRRSA model to help congruence scholars develop stronger theories and enhance scientific rigor in congruence research. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.485
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
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 head0.132
GPT teacher head0.437
Teacher spread0.305 · 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 designQualitative
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

Citations63
Published2022
Admission routes1
Has abstractyes

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