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Record W4214721985 · doi:10.1017/cbo9780511841163

What Science Offers the Humanities

2008· book· en· W4214721985 on OpenAlexaff
Edward Slingerland

Bibliographic record

VenueCambridge University Press eBooks · 2008
Typebook
Languageen
FieldPsychology
TopicLeadership, Courage, and Heroism Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsHumanismPostmodernismEpistemologySociologyHuman scienceHumanitiesDigital humanitiesMoralityNatural scienceConstructivism (international relations)PhilosophyPolitical sciencePoliticsLaw

Abstract

fetched live from OpenAlex

What Science Offers the Humanities examines some of the deep problems facing the study of culture. It focuses on the excesses of postmodernism, but also acknowledges serious problems with postmodernism's harshest critics. In short, Edward Slingerland argues that in order for the humanities to progress, its scholars need to take seriously contributions from the natural sciences - and particular research on human cognition - which demonstrate that any separation of the mind and the body is entirely untenable. The author provides suggestions for how humanists might begin to utilize these scientific discoveries without conceding that science has the last word on morality, religion, art, and literature. Calling into question such deeply entrenched dogmas as the 'blank slate' theory of nature, strong social constructivism, and the ideal of disembodied reason, What Science Offers the Humanities replaces the human-sciences divide with a more integrated approach to the study of culture.

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)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.996
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0040.028
Scholarly communication0.0110.013
Open science0.0010.002
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0080.002

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 head0.080
GPT teacher head0.256
Teacher spread0.176 · 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.

Study designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations187
Published2008
Admission routes1
Has abstractyes

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