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Record W7019121407

Episode 062: Situated Darwinism: Organism-centered evolution

2021· article· en· W7019121407 on OpenAlexaboutno aff

Bibliographic record

VenueThe Mathematics Enthusiast · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicPhilosophy and History of Science
Canadian institutionsnot available
Fundersnot available
KeywordsSituatedNatural selectionConstruct (python library)Selection (genetic algorithm)Focus (optics)Evolutionary theoryAbstraction
DOInot available

Abstract

fetched live from OpenAlex

Are genes the prime movers in evolution, or is causality distributed across multiple levels of organization? What role do organisms play in evolution? Could organismal agency, the propensity to respond actively to selective forces, affect standard evolutionary theory? On this episode, we talk with Denis Walsh, a professor and philosopher of biology at the University of Toronto, about his book Organisms, Agency, and Evolution. The Modern Synthesis, which combines Darwin’s theory of natural selection and Mendel’s theory of genetic inheritance, was a giant leap forward in our understanding of the evolution of populations. Denis argues, however, that the extreme abstraction required by the synthesis derails our understanding of evolution. What’s needed instead, he suggests, is renewed focus on organisms. Because organisms have agency—they in effect construct the environments they experience, which in turn affects how selection acts on them. This view reestablishes organisms – not genes – as the central unit of evolution, just as Darwin’s ‘struggle for existence’ emphasized. Cover Photo: Blue Dragon nudibranch (Pteraeolidia ianthina) by Saspotato (CC BY-NC-SA 2.0)

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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: Empirical · Consensus signal: none
Teacher disagreement score0.030
Threshold uncertainty score0.099

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0050.003
Scholarly communication0.0040.003
Open science0.0010.003
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0300.005

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 head0.052
GPT teacher head0.229
Teacher spread0.177 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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