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Record W4284882210 · doi:10.1017/9781108955638.006

The Evolution of Working Memory and Language

2022· book-chapter· en· W4284882210 on OpenAlexaff
Frederick L. Coolidge, Thomas A. Wynn

Bibliographic record

VenueCambridge University Press eBooks · 2022
Typebook-chapter
Languageen
FieldSocial Sciences
TopicLanguage and cultural evolution
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsLanguage evolutionWorking memoryCognitive scienceLinguisticsPsychologyCognitive psychologyRecallComputer scienceCognitionNeuroscience

Abstract

fetched live from OpenAlex

This chapter presents the hypothesis that working memory and language evolved in tandem. It reviews the evolutionary origins of each of the components of Baddeley's working memory model and their role in the evolution of language. The chapter reviews the gradualist position that language did evolve slowly from aurally directed early primate calls and notes that the primary purpose of language has always been communication. The chapter also presents the novel idea that the pragmatics of speech (the purposes of speech) also evolved in tandem with the evolution of working memory. The chapter also reviews the saltationist idea that something happened to language more recent than 100,000 years ago, and that is the release of the fifth pragmatic of speech, the subjunctive mood, which expresses wishes and ideas contrary to fact. The subjunctive mood required fully modern working memory capacity, sufficient phonological storage capacity, and an enhanced visuospatial sketchpad, which are also critically involved in episodic memory recall and simulation. The phenotypic result of this genotype meant that thought experiments could be conducted in a recursive manner. We propose that the fruits of Homo sapiens's cultural explosion, cave art, creative figurines, and highly ritualized burials, were the direct result of the wishes and imaginings that arise from subjunctive thinking and subjunctive language.

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)0.000
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.989
Threshold uncertainty score0.932

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.020
GPT teacher head0.213
Teacher spread0.193 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations2
Published2022
Admission routes1
Has abstractyes

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