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Record W3184969065 · doi:10.1017/epi.2021.23

On the Epistemic Costs of Friendship: Against the Encroachment View

2021· article· en· W3184969065 on OpenAlexaff
Catherine Rioux

Bibliographic record

VenueEpisteme · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicEpistemology, Ethics, and Metaphysics
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsFriendshipDoxastic logicDefeasible estateIrrationalityClosure (psychology)EpistemologyRealmObligationSocial psychologyPsychologyPolitical sciencePhilosophyRationalityLaw

Abstract

fetched live from OpenAlex

Abstract I defend the thesis that friendship can constitutively require epistemic irrationality against a recent, forceful challenge, raised by proponents of moral and pragmatic encroachment. Defenders of the “encroachment strategy” argue that exemplary friends who are especially slow to believe that their friends have acted wrongly are simply sensitive to the high prudential or moral costs of falsely believing in their friends’ guilt. Drawing on psychological work on epistemic motivation (and in particular on the notion of “need for closure”), I propose a different picture of what friendship requires in the doxastic realm. I argue that contrary to what the encroachment strategy suggests, exemplary friends’ belief formation ought not be guided by a concern with accuracy or error avoidance, but instead by a need to avoid a “specific closure” – namely, a need to avoid concluding in their friends’ guilt. I propose that exemplary friendship often generates a defeasible, doxastic obligation to exemplify such a need, despite its inherent corrupting effects on exemplary friends’ epistemic faculties.

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)0.009
metaresearch head score (Gemma)0.041
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: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.041
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0030.039
Scholarly communication0.0050.014
Open science0.0020.009
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0060.001

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 head0.066
GPT teacher head0.268
Teacher spread0.202 · 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

Citations4
Published2021
Admission routes1
Has abstractyes

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