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Record W2098762910 · doi:10.1027/1618-3169/a000043

Prime Proportion Affects Masked Priming of Fixed and Free-Choice Responses

2009· article· en· W2098762910 on OpenAlex
Glen E. Bodner, Rehman Mulji

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

VenueExperimental Psychology (formerly Zeitschrift für Experimentelle Psychologie) · 2009
Typearticle
Languageen
FieldDecision Sciences
TopicDecision-Making and Behavioral Economics
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPriming (agriculture)PsychologyPrime (order theory)Response primingCognitive psychologySocial psychologyCommunicationAudiologyNeuroscienceMathematicsBiologyCognitionLexical decision taskMedicineCombinatorics

Abstract

fetched live from OpenAlex

Left/right "fixed" responses to arrow targets are influenced by whether a masked arrow prime is congruent or incongruent with the required target response. Left/right "free-choice" responses on trials with ambiguous targets that are mixed among fixed trials are also influenced by masked arrow primes. We show that the magnitude of masked priming of both fixed and free-choice responses is greater when the proportion of fixed trials with congruent primes is .8 rather than .2. Unconscious manipulation of context can thus influence both fixed and free choices. Sequential trial analyses revealed that these effects of the overall prime context on fixed and free-choice priming can be modulated by the local context (i.e., the nature of the previous trial). Our results support accounts of masked priming that posit a memory-recruitment, activation, or decision process that is sensitive to aspects of both the local and global context.

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)0.003
metaresearch head score (Gemma)0.002
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.251
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0010.001
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 head0.147
GPT teacher head0.498
Teacher spread0.351 · 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