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Record W4380090834 · doi:10.1093/analys/anac085

Responding to How Things Seem: Bergmann on Scepticism and Intuition

2022· article· en· W4380090834 on OpenAlexafffund
Jennifer Nagel

Bibliographic record

VenueAnalysis · 2022
Typearticle
Languageen
FieldNeuroscience
TopicEmbodied and Extended Cognition
Canadian institutionsUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsIntuitionSkepticismEpistemologyPhilosophy

Abstract

fetched live from OpenAlex

Michael Bergmann’s important new book on scepticism is attractively systematic and thorough. He places familiar ideas under an exceptionally bright spotlight, exposing features we might not have noticed on casual survey. He draws out hidden consequences of his starting points with admirable courage, even when these consequences look like trouble for him. Before getting into this trouble, and some differences in how I would tackle it, I will begin by highlighting some ground we share. First, I like Bergmann’s fundamental epistemic optimism in the face of the sceptical challenge. When the radical sceptic suggests that close attention to our natural epistemic self-trust should erode it, I’ll agree with Bergmann that closer attention can vindicate it. Indeed, my optimism about epistemology extends all the way to holding that scrutiny of our instinctive ­epistemic self-trust can refine it, by alerting us in advance to some odd situations in which these natural instincts of ours can be expected to fail, and giving us a solid, non-sceptical understanding of just why this is so. Back on the positive side, I agree warmly with Bergmann that, in general, perceptual judgement and epistemic intuition are in good shape: our sensory faculties really do yield extensive knowledge of the world, and, moving up a level, our natural capacities for mindreading do yield extensive knowledge of the wide range of states of knowledge we possess (and, derivatively, states of justified belief – like Bergmann, I take knowledge to entail justified belief). I am not sure that Bergmann would favour the label ‘mindreading’ on our capacity for epistemic intuition, but I think that classifying it this way is entirely compatible with Bergmann’s commonsense Reidian approach. Understanding our instinctive mindreading capacities is one way of learning about ourselves, taking Bergmann’s ‘autodidactic’ turn (147), rather than attempting to convert the sceptical adversary directly. Perhaps some points can be scored against sloppy Academic sceptics who dogmatically maintain that knowledge is impossible – we can certainly challenge the positive claims they will need to make about the nature of knowledge, or the conditions of our existence, in order to argue for their repellent conclusion. But we should have no hope of directly converting the stronger Pyrrhonian sceptic, who simply maintains a chronic stance of questioning everything. There are dim prospects for ­constructing an anti-sceptical argument against him, starting from premises he will be bound to accept. As long as he is on the ball, the Pyrrhonian can keep raising an eyebrow at any attempt to formulate such premises, and the argument against him will never get going. Still, the power of an autodidactic approach should not be underestimated: for anyone who hasn’t already slipped into this ultimately sterile Pyrrhonian way of thinking, a healthy course of self-examination can fortify them against the threat of slipping into that trap in the future.

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)0.004
metaresearch head score (Gemma)0.013
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 score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.021
Scholarly communication0.0050.010
Open science0.0010.002
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0020.001

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 head0.027
GPT teacher head0.267
Teacher spread0.240 · 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

Citations0
Published2022
Admission routes2
Has abstractyes

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