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Record W1981534154 · doi:10.5840/monist201194210

Aristotle’s Pluralistic Realism

2011· article· ru· W1981534154 on OpenAlexaff
Devin Henry

Bibliographic record

VenueThe Monist · 2011
Typearticle
Languageru
FieldArts and Humanities
TopicClassical Philosophy and Thought
Canadian institutionsWestern University
Fundersnot available
KeywordsMonismRealismPhilosophyEpistemology

Abstract

fetched live from OpenAlex

In this paper I explore Aristotle’s views on natural kinds and the compatibility of pluralism and realism, a topic that has generated considerable interest among contemporary philosophers. I argue that, when it came to zoology, Aristotle denied that there is only one way of organizing the diversity of the living world into natural kinds that will yield a single, unified system of classification. Instead, living things can be grouped and regrouped into various cross-cutting kinds on the basis of objective similarities and differences in ways that subserve the explanatory context. Since the explanatory aims of zoology are diverse and variegated, the kinds it recognizes must be equally diverse and variegated. At the same time, there are certain constraints on which kinds can be selected. And those constraints derive more from the causal structure of the world than from the proclivities of the classifier (hence the realism). This distinguishes Aristotle’s version of pluralistic realism from those contemporary versions (like Dupré’s “promiscuous realism”) that treat all or most classifications of a given domain as equally legitimate and not just a sub-set of kinds recognized by the science that studies it. By contrast, Aristotle privileges scientifically important kinds on the basis of their role in causal investigations. On this picture natural kinds are those kinds with the sort of causal structure that allows them to enter into scientific explanations. In the final section I argue that Aristotle’s zoology should remain of interest to philosophers and biologists alike insofar as it combines a pluralistic form of realism with a rank-free approach to classification.

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)0.006
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 score0.006
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0050.022
Scholarly communication0.0050.007
Open science0.0010.005
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0030.001

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 head0.135
GPT teacher head0.229
Teacher spread0.095 · 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

Citations14
Published2011
Admission routes1
Has abstractyes

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