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Record W2020504551 · doi:10.3389/fpsyg.2013.00496

The role of consciousness in the phonological loop: hidden in plain sight

2013· article· en· W2020504551 on OpenAlexaff
Bradley R. Buchsbaum

Bibliographic record

VenueFrontiers in Psychology · 2013
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsBaycrest Hospital
Fundersnot available
KeywordsPsychologySightConsciousnessCognitionPerspective (graphical)Cognitive scienceCognitive psychologyAphasiaNeuroscienceArtificial intelligencePhysics

Abstract

fetched live from OpenAlex

We know from everyday experience that when we need to keep a small amount of verbal information "in mind" for a short period, an effective cognitive strategy is to silently rehearse the words. This basic cognitive strategy has been elegantly codified in Baddeley and colleagues model of verbal working memory, the phonological loop. Here we explore how the intuitive appeal of the phonological loop is grounded in the phenomenological experience of subvocal rehearsal as consisting of an interaction between an "inner voice" and an "inner ear." We focus particularly on how our intuitions about the phenomenological experience of "inner speech" might constrain or otherwise inform the functional architecture of information processing models of verbal working memory such as the phonological loop; and how, indeed, how ideas about consciousness may offer alternative explanations for the dual nature of inner speech in verbal working memory.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.019
Scholarly communication0.0040.014
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.022
GPT teacher head0.289
Teacher spread0.267 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations32
Published2013
Admission routes1
Has abstractyes

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