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Record W3210903325 · doi:10.18192/cjcs.vi8.5790

Knowing the Skeptic

2020· article· en· W3210903325 on OpenAlexvenueno aff
Michael McCreary

Bibliographic record

VenueConversations The Journal of Cavellian Studies · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicEpistemology, Ethics, and Metaphysics
Canadian institutionsnot available
Fundersnot available
KeywordsSkepticismNothingPhilosophyDreamEpistemologyCertaintyShadow (psychology)PsychoanalysisPsychology

Abstract

fetched live from OpenAlex

Descartes may have produced the paradigmatic image of modern philosophy when he donned his winter dressing gown, settled into his favorite armchair by the fire, and began a private meditation by wondering whether the flame in front of him were anything more than a dream. Like most skeptical recitals, the force of Descartes’ method arises through the mobilization of best cases for knowing; that is, through casting doubt on something so certain that one begins to question one’s ability to know anything at all. By impugning precisely those axioms we held most assured, Descartes demonstrates philosophy’s propensity to challenge our most fundamental assumptions, yet he simultaneously leverages the significance of the philosophical enterprise against more everyday or ordinary claims to knowledge, that of course the fire really burns. In doing so, Descartes opens up the possibility that a critic of skepticism will be more inclined to doubt the sanity of philosophical inquiry than to admit that the flame, or the greater external world, may be nothing more than a dream, or the conjuring of an evil demon. So the profundity or inanity of philosophy seems to turn on the whim of human temperament, and in particular, on my reaction to the idea that I may be mistaken about everything I claim to know.

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)0.015
metaresearch head score (Gemma)0.049
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: Other · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.079

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.049
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0080.039
Scholarly communication0.0160.016
Open science0.0010.005
Research integrity0.0100.018
Insufficient payload (model declined to judge)0.0060.004

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 head0.215
GPT teacher head0.312
Teacher spread0.096 · 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
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
Published2020
Admission routes1
Has abstractyes

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Same venueConversations The Journal of Cavellian StudiesSame topicEpistemology, Ethics, and MetaphysicsFrench-language works237,207