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Record W1991167048 · doi:10.15173/russell.v28i1.2131

Russell, Clifford, Whitehead and Differential Geometry

2008· article· en· W1991167048 on OpenAlexaffvenue
Sylvia Nickerson, Nicholas Griffin

Bibliographic record

VenueRussell the Journal of Bertrand Russell Studies · 2008
Typearticle
Languageen
FieldArts and Humanities
TopicPhilosophy, Science, and History
Canadian institutionsMcMaster UniversityUniversity of Toronto
Fundersnot available
KeywordsCurvatureEinsteinFoundations of geometrySubject (documents)Space (punctuation)Constant curvatureDifferential geometryPhilosophyGeneral relativityTheory of relativityTheoretical physicsEpistemologyGeometryMathematicsPhysicsMathematical physicsProjective geometry

Abstract

fetched live from OpenAlex

When Russell was fifteen, he was given a copy of W.K. Clifford’s The Common Sense of the Exact Sciences (1886). Russell later recalled reading it immediately “with passionate interest and with an intoxicating delight in intellectual clarification”. Why then, when Russell wrote An Essay on the Foundations of Geometry (1897), did he choose to defend spaces of homogeneous curvature as a priori? Why was he almost completely silent thereafter on the subject of Clifford, and his writings on geometry and space? We suggest that Russell may have avoided Clifford’s hypothesis that space had heterogeneous curvature because it seemed impossible to reconcile a coherent theory of measurement with a space of variable curvature. Whitehead objected to Einstein’s general theory of relativity on this basis, formulating an alternate theory that preserved the constant curvature of space and, therefore, a familiar sense of measurement. After Einstein’s general theory, Russell chose to distance himself from the position he argued in the Essay.

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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0030.016
Scholarly communication0.0040.006
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0060.001

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 head0.050
GPT teacher head0.249
Teacher spread0.198 · 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

Citations1
Published2008
Admission routes2
Has abstractyes

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