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Flow as Spontaneous Thought

2018· book· en· W2795820436 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

VenueOxford University Press eBooks · 2018
Typebook
Languageen
FieldPsychology
TopicFlow Experience in Various Fields
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsFlow (mathematics)CognitionPsychologyCognitive scienceCognitive psychologyEpistemologyMechanicsPhilosophyNeuroscience

Abstract

fetched live from OpenAlex

Flow is an experience encountered in many areas of human endeavor; it is reported by athletes and artists, writers and thinkers. Paradoxically, it appears to involve significant energy expenditure, and yet it is reported to feel almost effortless. It is a prototypical instance of spontaneous thought. The flow experience has been extensively documented and studied by many scholars, most prominently Csikszentmihalyi, who characterized it as “optimal experience.” This chapter builds on the work of Csikszentmihalyi and others by providing a cognitive scientific account of flow, a framework that organizes and integrates the various cognitive processes and features that serve to make flow an optimal experience. In particular, it is argued that flow is characterized by a dynamic cascade of insight, coupled with enhanced implicit learning. This model seeks to integrate the phenomenological accounts of flow with the existing body of cognitive research.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.471
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0020.001
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 head0.019
GPT teacher head0.251
Teacher spread0.232 · 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