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Record W2149704867 · doi:10.1353/cjp.2007.0025

Teleology Without Tears: Aristotle and the Role of Mechanistic Conceptions of Organisms

2007· article· en· W2149704867 on OpenAlexaff
Sylvia Berryman

Bibliographic record

VenueCanadian Journal of Philosophy · 2007
Typearticle
Languageen
FieldArts and Humanities
TopicClassical Philosophy and Thought
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsTeleologyEpistemologyNatural (archaeology)Context (archaeology)Natural philosophyPhilosophyAncient GreekAncient philosophyField (mathematics)History

Abstract

fetched live from OpenAlex

In this paper I outline a role for mechanistic conceptions of organisms in ancient Greek natural philosophy, especially the study of organisms. By ‘mechanistic conceptions’ I mean the use of ideas and techniques drawn from the field of mechanics to investigate the natural world. ‘Mechanistic conceptions’ of organisms in ancient Greek philosophy, then, are those that draw on the ancient understanding of the field called ‘mechanics’ — hê mêchanikê technê —to investigate living things, rather than those bearing some perceived similarity to modern notions of ‘the mechanical.’ I have argued elsewhere that evidence of mechanistic conceptions of the natural world can be found, not only among seventeenth and eighteenth century ‘mechanical philosophers,’ but also—albeit in vestigial form — in some ancient Greek texts. Unfortunately, these reports are slight, often by detractors of this approach, and offer only clues as to the motivational context for employing these mechanical conceptions. Here, my purpose is to suggest what role they might have played in the history of natural philosophy.

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 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 score0.005
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.038
Scholarly communication0.0040.014
Open science0.0010.003
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0050.001

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 head0.015
GPT teacher head0.203
Teacher spread0.188 · 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

Citations52
Published2007
Admission routes1
Has abstractyes

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