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Record W1862132001 · doi:10.1017/cbo9780511541698.003

The definition of human nature

2004· book-chapter· en· W1862132001 on OpenAlexaff
Merlin W. Donald

Bibliographic record

VenueCambridge University Press eBooks · 2004
Typebook-chapter
Languageen
FieldNeuroscience
TopicNeuroethics, Human Enhancement, Biomedical Innovations
Canadian institutionsQueen's UniversityUniversity of Toronto
Fundersnot available
KeywordsFoundation (evidence)EpistemologyNatural lawConstruct (python library)Natural (archaeology)DarwinismContext (archaeology)SociologyDarwin (ADL)LawEnvironmental ethicsPolitical sciencePhilosophyGeographyComputer science

Abstract

fetched live from OpenAlex

Our definition of human nature gives us a conceptual foundation for our ideas about human rights, individual responsibility, and personal freedom. These ideas were originally derived from the liberal humanities, and are ultimately the secular modern descendants of the concept of a ‘natural law’ based on earlier religious and philosophical traditions. In this context, this is not a trivial exercise. It provides a conceptual foundation for our legal system, as well as our constitutional protections of human rights. Since the time of Charles Darwin there have been many attempts to define human nature in more scientific terms. In effect, this has amounted to an attempt to derive a new kind of natural law, based largely on scientific evidence, and especially on the theory of evolution. Here I am not speaking of Social Darwinism, an earlier intellectual movement that naively tried to extrapolate the laws of natural selection to human society, but of more recent empirical attempts to construct a culturally universal description of the human condition, and to explain it in terms of evolution and genetics. In such attempts, human nature is usually defined as having been fixed when our species evolved in the Upper Palaeolithic, and this suggests that we have been genetically engineered to survive under the special conditions of late Stone Age civilisation. This raises the disconcerting possibility that human nature might prove to be maladaptive in today's high-tech, fast-moving, urbanised world. On the other hand, the logic leading to this conclusion is not compelling.

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)0.002
metaresearch head score (Gemma)0.002
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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0030.020
Scholarly communication0.0060.007
Open science0.0010.003
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0090.003

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 head0.068
GPT teacher head0.265
Teacher spread0.197 · 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".

Quick stats

Citations49
Published2004
Admission routes1
Has abstractyes

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Same venueCambridge University Press eBooksSame topicNeuroethics, Human Enhancement, Biomedical InnovationsFrench-language works237,207