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Record W2475166867 · doi:10.18192/cjcs.v0i4.1727

Cynical Self-Doubt and the Grounds of Sympathy

2016· article· en· W2475166867 on OpenAlexvenueno aff
Sam Cardoen

Bibliographic record

VenueConversations The Journal of Cavellian Studies · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicWittgensteinian philosophy and applications
Canadian institutionsnot available
Fundersnot available
KeywordsSkepticismSympathyEpistemologyArgument (complex analysis)PhilosophyPsychologySocial psychologyMedicine

Abstract

fetched live from OpenAlex


 
 
 
 
 The foundational essay of Stanley Cavell’s oeuvre, “Knowing and Acknowledging,” prepares the author’s continued interest in sceptical doubt about the existence of other minds as well as his specific approach to this particular philosophical problem. One useful way of approaching “Knowing and Acknowledging” is to suggest that it addresses the other minds sceptic so as to excavate alongside him the underlying ground from which his doubt about the existence of other minds emerges. Cavell, in other words, appears to compose his argument in such a way as to lead the sceptic along a series of steps that demonstrate that his sceptical doubt does not simply exist as a self-contained or self-standing problem. In doing so, Cavell traces the emergence of sceptical doubt about other minds to a specific anxiety about our reliance on expressions of sympathy as a way of responding to the suffering of others. Cavell argues that the sceptic subsequently intellectualizes this anxiety into sceptical doubt. Cavell explicitly does not seek to refute the sceptic; he even accepts that the sceptic’s intellectual doubt is, in its way, valid. For Cavell, to try to straightforwardly refute sceptical doubt is simply to accept the terms on which it presents itself, and thereby to extend the sceptic’s view. Instead, Cavell tries to get the sceptic to a point where he will regard the nature, and the origins, of his doubt differently than he did before.
 
 
 

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.513
Threshold uncertainty score0.582

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 studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.042
GPT teacher head0.247
Teacher spread0.205 · 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 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
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueConversations The Journal of Cavellian StudiesSame topicWittgensteinian philosophy and applicationsFrench-language works237,207