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Record W2100826268 · doi:10.1027/1015-5759.24.4.218

Response Interference as a Mechanism Underlying Implicit Measures

2008· article· en· W2100826268 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEuropean Journal of Psychological Assessment · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Intergroup Psychology
Canadian institutionsWestern University
Fundersnot available
KeywordsPsychologyImplicit-association testCognitive psychologyImplicit attitudePriming (agriculture)Mechanism (biology)Construct validityMediationAssociation (psychology)Task (project management)Construct (python library)Social psychologyPsychometricsDevelopmental psychologyComputer science

Abstract

fetched live from OpenAlex

Over the last decade, implicit measures of mental associations (e.g., Implicit Association Test, sequential priming) have become increasingly popular in many areas of psychological research. Even though successful applications provide preliminary support for the validity of these measures, their underlying mechanisms are still controversial. The present article addresses the role of a particular mechanism that is hypothesized to mediate the influence of activated associations on task performance in many implicit measures: response interference (RI). Based on a review of relevant evidence, we argue that RI effects in implicit measures depend on participants’ attention to association-relevant stimulus features, which in turn can influence the reliability and the construct validity of these measures. Drawing on a moderated-mediation model (MMM) of task performance in RI paradigms, we provide several suggestions on how to address these problems in research using implicit measures.

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.

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)0.005
metaresearch head score (Gemma)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.705
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.207
GPT teacher head0.455
Teacher spread0.248 · 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