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Record W2035535055 · doi:10.1163/221057012x627249

Characterizing Skepticism’s Import

2012· article· en· W2035535055 on OpenAlexaff
Jill Rusin

Bibliographic record

VenueInternational Journal for the Study of Skepticism · 2012
Typearticle
Languageen
FieldArts and Humanities
TopicEpistemology, Ethics, and Metaphysics
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsSkepticismEpistemologyNormativePhilosophyContextualismInterpretation (philosophy)

Abstract

fetched live from OpenAlex

This paper discusses a common contemporary characterization of skepticism and skeptical arguments—that their real importance is instrumental, that they “drive progress in philosophy.” I explore two possible contrasts to the idea that skepticism’s significance is thus wholly methodological. First, I recall for the reader a range of views that can be understood as ‘truth in skepticism’ views. These concessive views are those most clearly at odds with the idea that skepticism is false, but instrumentally valuable. Considering the contributions of such ‘truth in skepticism’ theorists, I argue, shows that the good of furthering philosophical progress is partly achieved by the work of those who would reject the ‘merely methodological’ view of skepticism’s import. While this shows such a view of skepticism’s import to be partially self-effacing, it is not therefore incoherent. Rather, the characterization is revealed to be wedded to particular diagnoses of skepticism, and not independently innocuous or neutral. Second, I discuss the idea that the ‘merely methodological’ characterization of skepticism’s import draws a contrast with philosophical positions or theses that are supposed to have practical teeth. Here, I think the danger of acquiescing too readily to this view is that the normative import of skeptical arguments is obscured. At a time when discussions of the value of knowledge are in ascendency, this in particular seems a loss—a route from consideration of skeptical arguments to broader normative questions worth keeping open is rather more obscured than opened up. Any radically revisionary outcome of an encounter with skepticism is less likely, led by such an understanding, just when there is opportunity instead to connect up with broad questions of epistemic value. For these reasons I argue the characterization is not one to too readily, unthinkingly, endorse.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.787
Threshold uncertainty score0.381

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.111
GPT teacher head0.350
Teacher spread0.239 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations0
Published2012
Admission routes1
Has abstractyes

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