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Record W2758533448 · doi:10.3389/fnins.2017.00519

Evolutionary Musicology Meets Embodied Cognition: Biocultural Coevolution and the Enactive Origins of Human Musicality

2017· review· en· W2758533448 on OpenAlexafffund
Dylan van der Schyff, Andrea Schiavio

Bibliographic record

VenueFrontiers in Neuroscience · 2017
Typereview
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsSimon Fraser University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsEmbodied cognitionAdaptation (eye)MusicologyCoevolutionCognitive scienceRelevance (law)MusicalityField (mathematics)SociologyCognitionEpistemologyPsychologyPhilosophyEcologyBiologyMusicalNeuroscienceArt

Abstract

fetched live from OpenAlex

Despite evolutionary musicology’s interdisciplinary nature, and the diverse methods it employs, the field has nevertheless tended to divide into two main positions. Some argue that music should be understood as a naturally selected adaptation, while others claim that music is a product of culture with little or no relevance for the survival of the species. We review these arguments, suggesting that while interesting and well-reasoned positions have been offered on both sides of the debate, the nature-or-culture (or adaptation vs. non-adaptation) assumptions that have traditionally driven the discussion have resulted in a problematic either/or dichotomy. We then consider an alternative ‘biocultural’ proposal that appears to offer a way forward. As we discuss, this approach draws on a range of research in theoretical biology, archeology, neuroscience, embodied and ecological cognition, and dynamical systems theory, positing a more integrated model that sees biological and cultural dimensions as aspects of the same evolving system. Following this, we outline the enactive approach to cognition, discussing the ways it aligns with the biocultural perspective. Put simply, the enactive approach posits a deep continuity between mind and life, where cognitive processes are explored in terms of how self-organizing living systems enact relationships with the environment that are relevant to their survival and well-being. It highlights the embodied and ecologically situated nature of living agents, as well as the active role they play in their own developmental processes. Importantly, the enactive approach sees cognitive and evolutionary processes as driven by a range of interacting factors, including the socio-cultural forms of activity that characterize the lives of more complex creatures such as ourselves. We offer some suggestions for how this approach might enhance and extend the biocultural model. To conclude we briefly consider the implications of this approach for practical areas such as music education.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.982
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.009
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0000.001
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 head0.149
GPT teacher head0.382
Teacher spread0.233 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations65
Published2017
Admission routes2
Has abstractyes

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