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Record W3193313335 · doi:10.1007/s11097-021-09762-x

Flow and the dynamics of conscious thought

2021· article· en· W3193313335 on OpenAlexafffund
Joshua Shepherd

Bibliographic record

VenuePhenomenology and the Cognitive Sciences · 2021
Typearticle
Languageen
FieldPsychology
TopicFlow Experience in Various Fields
Canadian institutionsCarleton University
FundersH2020 European Research CouncilCanadian Institute for Advanced Research
KeywordsPhenomenology (philosophy)Construct (python library)Philosophy of mindEpistemologyConsciousnessPsychologyCognitive scienceFlow (mathematics)CognitionAgency (philosophy)SociologyMetaphysicsComputer sciencePhilosophyMechanicsNeuroscience

Abstract

fetched live from OpenAlex

Abstract The flow construct has been influential within positive psychology, sport psychology, the science of consciousness, the philosophy of agency, and popular culture. In spite of its longstanding influence, it remains unclear [a] how the constituents of the flow state ‘hang together’—how they relate to each other causally and functionally—[b] in what sense flow is an ‘optimal experience,’ and [c] how best to describe the unique phenomenology of the flow state. As a result, difficulties persist for a clear understanding of the flow state’s structure and function. After explicating the standard view of the flow construct (section one), I articulate several basic questions regarding its nature and functional roles (section two), and I argue that these questions are best answered by integrating flow within broader streams of research on the dynamics of thought, on cognitive control resource allocation, and on creative thought (sections three and four).

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)0.002
metaresearch head score (Gemma)0.007
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 score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.014
Scholarly communication0.0040.008
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.027
GPT teacher head0.321
Teacher spread0.294 · 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

Citations25
Published2021
Admission routes2
Has abstractyes

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Same venuePhenomenology and the Cognitive SciencesSame topicFlow Experience in Various FieldsFrench-language works237,207