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Record W2108763988 · doi:10.1080/09541440701728623

Why do words hurt? Content, process, and criterion shift accounts of verbal overshadowing

2008· article· en· W2108763988 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

VenueThe European Journal of Cognitive Psychology · 2008
Typearticle
Languageen
FieldPsychology
TopicEmotions and Moral Behavior
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPsychologyPhenomenonCognitive psychologyTask (project management)Content (measure theory)Process (computing)Cognitive scienceEpistemologyComputer science

Abstract

fetched live from OpenAlex

Verbal overshadowing describes the phenomenon in which verbalisation negatively affects performance on a task related to the verbalised material. Within the verbal overshadowing literature, three accounts exist which attempt to explain this phenomenon: content, processing, and criterion accounts. The content account refers to the notion that the specific contents of verbalisation interfere with later performance, processing refers to a proposed shift in processing caused by verbalisation, and criterion deals with the possibility that verbalisation leads to a reliance on more conservative choosing. The current manuscript reviews evidence for the existing accounts, while describing advantages and disadvantages of each account and attempting to reconcile these various accounts. The authors provide a framework for understanding verbal overshadowing as caused by one unified mechanism, or several. Finally, an outline for future research is suggested that should aid in reconciling the existing accounts for verbal overshadowing.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.554
Threshold uncertainty score0.489

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.091
GPT teacher head0.363
Teacher spread0.272 · 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