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Record W3142617309 · doi:10.1080/1047840x.2021.1889312

There’s Nothing Social about Social Priming: Derailing the “Train Wreck”

2021· article· en· W3142617309 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

VenuePsychological Inquiry · 2021
Typearticle
Languageen
FieldPsychology
TopicAction Observation and Synchronization
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPriming (agriculture)PsychologyConstruct (python library)Social psychologyCognitive psychologyReliability (semiconductor)Social cognitionCognitionNeuroscienceComputer science

Abstract

fetched live from OpenAlex

Failures to replicate high-profile priming effects have raised questions about the reliability of so-called “social priming” phenomena. However, not only are many of the relevant studies not particularly social in nature, but other robust priming effects that are clearly social in nature do not count as social priming. Most importantly, the focus on the supposedly social aspect of the work has obscured factors that help to account for the relative reliability of priming effects. Here, we examine the construct of social priming, describe some simple demonstrations on the role of experimental design in priming reproducibility, and discuss future avenues for building a better understanding of priming. We conclude that the term “social priming” should be laid to rest, and that it is time to move past arguments about the reliability of specific effects and shift our energy to building theories that help us better understand the mechanisms underlying priming effects.

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 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 score0.653
Threshold uncertainty score0.991

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0100.001

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 head0.279
GPT teacher head0.450
Teacher spread0.172 · 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