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Record W4391923459 · doi:10.1159/000537908

The Roots of Science, Technology, Engineering, and Mathematics: What Are the Evolutionary and Neural Bases of Human Mathematics and Technology?

2024· article· en· W4391923459 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

VenueBrain Behavior and Evolution · 2024
Typearticle
Languageen
FieldNeuroscience
TopicHemispheric Asymmetry in Neuroscience
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsMathematics educationEngineeringComputer scienceManagement scienceMathematics

Abstract

fetched live from OpenAlex

INTRODUCTION: Neural exaptations represent descent via transitions to novel neural functions. A primary transition in human cognitive and neural evolution was from a predominantly socially oriented primate brain to a brain that also instantiates and subserves science, technology, and engineering, all of which depend on mathematics. Upon what neural substrates and upon what evolved cognitive mechanisms did human capacities for science, technology, engineering, and mathematics (STEM), and especially its mathematical underpinnings, emerge? Previous theory focuses on roles for tools, language, and arithmetic in the cognitive origins of STEM, but none of these factors appears sufficient to support the transition. METHODS: In this article, I describe and evaluate a novel hypothesis for the neural origins and substrates of STEM-based cognition: that they are based in human kinship systems and human maximizing of inclusive fitness. RESULTS: The main evidence for this hypothesis is threefold. First, as demonstrated by anthropologists, human kinship systems exhibit complex mathematical and geometrical structures that function under sets of explicit rules, and such systems and rules pervade and organize all human cultures. Second, human kinship underlies the core algebraic mechanism of evolution, maximization of inclusive fitness, quantified as personal reproduction plus the sum of all effects on reproduction of others, each multiplied by their coefficient of relatedness to self. This is the only "natural" equation expected to be represented in the human brain. Third, functional imaging studies show that kinship-related cognition activates frontal-parietal regions that are also activated in STEM-related tasks. In turn, the decision-making that integrates kinship levels with costs and benefits from alternative behaviors has recently been shown to recruit the lateral septum, a hub region that combines internal (from the prefrontal cortex, amygdala, and other regions) and external information relevant to social behavior, using a dedicated subsystem of neurons specific to kinship. CONCLUSIONS: Taken together, these lines of evidence suggest that kinship systems and kin-associated behaviors may represent exaptations for the origin of human STEM.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.601
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.005
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 head0.016
GPT teacher head0.271
Teacher spread0.256 · 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