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Abduction and Modality

2010· article· en· W2122099267 on OpenAlexaff
Stephen Biggs

Bibliographic record

VenuePhilosophy and Phenomenological Research · 2010
Typearticle
Languageen
FieldPsychology
TopicPhilosophy and Theoretical Science
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMetaphysicsModalModality (human–computer interaction)EpistemologyInferencePhilosophyPhilosophy of mindComputer sciencePsychologyCognitive scienceArtificial intelligence

Abstract

fetched live from OpenAlex

This paper introduces a modal epistemology that centers on inference to the best explanation (i.e. abduction). In introducing this abduction‐centered modal epistemology, the paper has two main goals. First, it seeks to provide reasons for pursuing an abduction‐centered modal epistemology by showing that this epistemology aids a popular stance on the mind‐body problem and allows an appealing approach to modality. Second, the paper seeks to show that an abduction‐centered modal epistemology can work by showing that abduction can establish claims about necessity/possibility (i.e. modal claims)—where ‘necessity’ and ‘possibility’ denote metaphysical necessity and possibility, ways things may or may not have been given how they actually are.

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)0.012
metaresearch head score (Gemma)0.019
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 score0.012
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.019
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0040.002
Science and technology studies0.0030.031
Scholarly communication0.0060.014
Open science0.0030.008
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0080.001

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 head0.198
GPT teacher head0.452
Teacher spread0.254 · 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

Citations38
Published2010
Admission routes1
Has abstractyes

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