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Record W4392292889 · doi:10.1017/epi.2024.6

Epistemic Complicity

2023· article· en· W4392292889 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEpisteme · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicEpistemology, Ethics, and Metaphysics
Canadian institutionsBrandon University
Fundersnot available
KeywordsComplicityWrongdoingEpistemologyAgency (philosophy)PhilosophyCollective responsibilitySociologyPolitical scienceLawTheology

Abstract

fetched live from OpenAlex

Abstract There is a widely accepted distinction between being directly responsible for a wrongdoing versus being somehow indirectly or vicariously responsible for the wrongdoing of another person or collective. Often this is couched in analyses of complicity, and complicity's role in the relationship between individual and collective wrongdoing. Complicity is important because, inter alia, it allows us to make sense of individuals who may be blameless or blameworthy to a relatively low degree for their immediate conduct, but are nevertheless blameworthy to a higher degree for their implication in some larger (or another person's) wrongdoing. In this paper, I argue that there is a distinctively epistemic kind of complicity. First, I motivate the distinction between direct and vicarious responsibility with three interlocking arguments, respectively appealing to: (i) the structure of rational agency; (ii) linguistic considerations; (iii) the role of ‘principal' vs. ‘accomplice’ in legal doctrine. I show how these arguments naturally extend to the epistemic domain, motivating an epistemic form of vicarious responsibility. I then examine complicity as a mechanism of vicarious epistemic responsibility. To fill this out, I engage with an epistemic analogue of the debate about the role of intention versus causal contribution in complicity. I propose a Casual Account of Epistemic Complicity, arguing that it accommodates a wide range of cases, and enables fine-grained explanations of degrees of culpability for epistemic complicity. With an adequate account of epistemic complicity on hand, we can explain what is objectionable about an important class of epistemic agent who, on an individual level, may be epistemically blameless or blameworthy to a relatively low degree, but whose relation to other individuals or collectives nevertheless makes them epistemically blameworthy to a higher degree. I explore some broader implications of this result.

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.876
Threshold uncertainty score0.995

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.006

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 head0.144
GPT teacher head0.295
Teacher spread0.152 · 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