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Record W7003485373

Berkeley's Bodies

2013· dissertation· en· W7003485373 on OpenAlexvenueno aff

Bibliographic record

VenueLibrary and Archives Canada (Government of Canada) · 2013
Typedissertation
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCell Image Analysis Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsNothingMeaning (existential)SkepticismContext (archaeology)Reflexive pronounCommon senseMechanism (biology)Subject (documents)Property (philosophy)
DOInot available

Abstract

fetched live from OpenAlex

George Berkeley (1685-1753) defends immaterialism, the view that there is no such thing as matter. In place of matter, what exists are only minds and ideas. Berkeley also styles himself a defender of common sense. From early on many of Berkeley's readers doubted that these two commitments could be reconciled. I consider Berkeley's joint commitment to immaterialism and common sense in respect of two philosophical theses. (1) Berkeley argues against a version of scepticism that bodies are single collections, constituted by many ideas placed in certain relations, and veridically sensed by finite minds. I identify these collections as Berkeley's enigmatic archetypes. (2) Berkeley argues that finite minds are able to act causally upon their own bodies by nothing more than an act of will. Both of these theses are defended in the context of immaterialism, and Berkeley persuasively presents them as elements of common sense. I reconstruct Berkeley's arguments for these theses, and suggest that he succeeds in reconciling immaterialism and common sense in these areas. My account draws on previous research, but I introduce a single mechanism to understand both theses. I call this mechanism overlap. On Berkeley's view, finite minds represent bodies by constructing representing-collections that are intended to resemble body-collections. However, these representing-collections overlap with body-collections, meaning that they share members which are numerically the same. My account of (1) depends on the fact that sensed ideas are in the overlapping area, and therefore represent the body-collection exactly as it is. My account of (2) depends on supposing that the causal powers of finite minds are exercised on ideas in the area of overlap, and thus they act on ideas that are accessible to them but are also constituent parts of bodies.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.022
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0070.016
Scholarly communication0.0070.007
Open science0.0010.004
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0220.006

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 head0.002
GPT teacher head0.157
Teacher spread0.155 · 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 designNot applicable
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

Citations0
Published2013
Admission routes1
Has abstractyes

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Same venueLibrary and Archives Canada (Government of Canada)Same topicCell Image Analysis TechniquesFrench-language works237,207