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Record W2135970549 · doi:10.1177/0963721414551165

The Changing Face of Attentional Development

2015· article· en· W2135970549 on OpenAlexaff
Jelena Ristic, James T. Enns

Bibliographic record

VenueCurrent Directions in Psychological Science · 2015
Typearticle
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsUniversity of British ColumbiaMcGill University
Fundersnot available
KeywordsPsychologyPerspective (graphical)ConsciousnessCognitive psychologyTRACE (psycholinguistics)Face (sociological concept)Cognitive scienceQUIETNeuroscienceComputer scienceArtificial intelligenceSociology

Abstract

fetched live from OpenAlex

The field of attentional development has recently undergone a quiet revolution. Attention is no longer being studied as a static gatekeeper of consciousness and action; instead, it is being reconceptualized as a dynamic system that both influences and is influenced by the interactions between individuals and their environments. In this review, we first revisit the conventional understanding of attentional development, showing that a large body of research conducted using a handful of laboratory tasks failed to deliver deep theoretical insights. We then trace the revolution to show how investigators have been changing their research questions in response to this impasse. Finally, we speculate on what the future of attentional development research might look like from this emerging dynamic perspective.

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 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)0.001
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 score0.804
Threshold uncertainty score0.557

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.002
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 head0.402
GPT teacher head0.500
Teacher spread0.098 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations35
Published2015
Admission routes1
Has abstractyes

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