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Rationalism and Relativism

2003· book-chapter· en· W336493165 on OpenAlexaff
Bruce G. Trigger

Bibliographic record

VenueCambridge University Press eBooks · 2003
Typebook-chapter
Languageen
FieldSocial Sciences
TopicEvolutionary Game Theory and Cooperation
Canadian institutionsMcGill University
Fundersnot available
KeywordsCONTESTMaterialismRelativismEpistemologyDarwinismCultural relativismEnvironmental ethicsSociologyRationalismSocial sciencePolitical sciencePhilosophyLawHuman rights

Abstract

fetched live from OpenAlex

The most important issue confronting the social sciences is the extent to which human behaviour is shaped by factors that operate cross-culturally as opposed to factors that are unique to particular cultures. In part this debate addresses to what degree and in what ways human behaviour is influenced by calculations of self-interest that all human beings make in a similar manner as opposed to particularistic, culturally conditioned, and largely autonomous modes of conceiving reality. Marshall Sahlins (1976: ix) has labelled this confrontation the ‘contest between the practical and the meaningful’. The debate goes beyond this, however, to consider to what extent humans may be biologically predisposed to understand reality and behave in similar ways. This debate has pitted materialists against idealists, behaviourists against advocates of cultural studies, processual archaeologists against postprocessual ones, and traditional cultural ecologists, as well as Darwinian archaeologists and sociobiologists, against neo-Boasian postmodernists. It has also split what remains of academic Marxism into two warring camps. At the centre of this debate is a fundamental question: given the biological similarities and the cultural diversity of human beings, how much the same or how differently are they likely to behave under analogous circumstances? The answer to this question is crucial for understanding human behaviour and cultural change and for shaping the future course of human development (Trigger 1998a). In recent years theoretical positions have been elaborated with great subtlety and refinement, but there is no sign of consensus.

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)0.004
metaresearch head score (Gemma)0.005
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 score0.007
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.023
Scholarly communication0.0050.007
Open science0.0010.002
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0070.002

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 head0.024
GPT teacher head0.219
Teacher spread0.195 · 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

Citations9
Published2003
Admission routes1
Has abstractyes

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Same venueCambridge University Press eBooksSame topicEvolutionary Game Theory and CooperationFrench-language works237,207