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Why the Mind Wanders

2018· book· en· W2796262914 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
FieldNeuroscience
TopicEmbodied and Extended Cognition
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsDefault mode networkTask (project management)Episodic memoryMind-wanderingCognitive psychologyContent (measure theory)CognitionProduction (economics)DefaultMechanism (biology)Cognitive sciencePsychologyPhilosophy of mindChronesthesiaSemantic memoryMode (computer interface)Computer scienceEpistemologyPhilosophyNeuroscienceMathematicsEconomics

Abstract

fetched live from OpenAlex

This chapter offers a functional account of why the mind—when free from the demands of a task or the constraints of heightened emotions—tends to wander from one topic to another, in a ceaseless and seemingly random fashion. We propose the default variability hypothesis, which builds on William James’s phenomenological account of thought as a form of mental locomotion, as well as on recent advances in cognitive neuroscience and computational modeling. Specifically, the default variability hypothesis proposes that the default mode of mental content production yields the frequent arising of new mental states that have heightened variability of content over time. This heightened variability in the default mode of mental content production may be an adaptive mechanism that (1) enhances episodic memory efficiency through de-correlating individual episodic memories from one another via temporally spaced reactivations, and (2) facilitates semantic knowledge optimization by providing optimal conditions for interleaved learning.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.581
Threshold uncertainty score0.900

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.043
GPT teacher head0.222
Teacher spread0.178 · 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