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Record W2047410999 · doi:10.1177/1745691613483774

Theory and Metatheory in the Study of Dual Processing

2013· article· en· W2047410999 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

VenuePerspectives on Psychological Science · 2013
Typearticle
Languageen
FieldDecision Sciences
TopicDecision-Making and Behavioral Economics
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMetatheoryFalsifiabilityDual (grammatical number)ConstructiveEpistemologyTask (project management)TestabilityProcess (computing)CategorizationConfusionDuality (order theory)Computer sciencePsychologyPhilosophyMathematics

Abstract

fetched live from OpenAlex

In this article, we respond to the four comments on our target article. Some of the commentators suggest that we have formulated our proposals in a way that renders our account of dual-process theory untestable and less interesting than the broad theory that has been critiqued in recent literature. Our response is that there is a confusion of levels. Falsifiable predictions occur not at the level of paradigm or metatheory-where this debate is taking place-but rather in the instantiation of such a broad framework in task level models. Our proposal that many dual-processing characteristics are only correlated features does not weaken the testability of task-level dual-processing accounts. We also respond to arguments that types of processing are not qualitatively distinct and discuss specific evidence disputed by the commentators. Finally, we welcome the constructive comments of one commentator who provides strong arguments for the reality of the dual-process distinction.

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)0.013
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.914
Threshold uncertainty score0.547

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.153
GPT teacher head0.487
Teacher spread0.334 · 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