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Morality: An Evolutionary Account

2008· article· en· W2132071493 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

VenuePerspectives on Psychological Science · 2008
Typearticle
Languageen
FieldNeuroscience
TopicPsychology of Moral and Emotional Judgment
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsMoralitySocial cognitive theory of moralityMoral disengagementMoral developmentMoral reasoningArgumentation theoryPsychologyConscienceInstinctEpistemologySocial psychologyDarwin (ADL)Computer sciencePhilosophy

Abstract

fetched live from OpenAlex

Refinements in Darwin's theory of the origin of a moral sense create a framework equipped to organize and integrate contemporary theory and research on morality. Morality originated in deferential, cooperative, and altruistic "social instincts," or decision-making strategies, that enabled early humans to maximize their gains from social living and resolve their conflicts of interest in adaptive ways. Moral judgments, moral norms, and conscience originated from strategic interactions among members of groups who experienced confluences and conflicts of interest. Moral argumentation buttressed by moral reasoning is equipped to generate universal and impartial moral standards. Moral beliefs and standards are products of automatic and controlled information-processing and decision-making mechanisms. To understand how people make moral decisions, we must understand how early evolved mechanisms in the old brain and recently evolved mechanisms in the new brain are activated and how they interact. Understanding what a sense of morality is for helps us understand what it is.

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, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.963
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.004
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.210
GPT teacher head0.384
Teacher spread0.174 · 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