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Record W3213619021 · doi:10.1093/pq/pqab058

Between Deflationism and Inflationism: A Moderate View on Truth and Reference

2021· article· en· W3213619021 on OpenAlexaff
Graham Seth Moore

Bibliographic record

VenueThe Philosophical Quarterly · 2021
Typearticle
Languageen
FieldPsychology
TopicPhilosophy and Theoretical Science
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsEpistemologyPhilosophySkepticismVariety (cybernetics)Contrast (vision)Order (exchange)ReductionismSpace (punctuation)Computer scienceLinguisticsEconomicsArtificial intelligence

Abstract

fetched live from OpenAlex

Abstract This essay argues for a two-part thesis concerning the deflationist theories of truth and reference. First, I identify two points of contrast between the deflationist theories and their traditional inflationary opponents: (1) they each employ different orders of explanation for the variety of semantic phenomena, and (2) the inflationist is typically taken to be beholden to a reductive explanation of reference, whereas the deflationist is doubtful of this project. Secondly, I argue that these two points of contrast need not come together to exhaust the space of possible views. There is room for a plausible middle ground: a moderate version of inflationism. My moderate inflationism will reject the deflationist's order of explanation, so it counts as genuinely inflationary. However, it also rejects the reductionist ambitions of the earlier inflationists, so it isn’t an apt target for deflationary scepticism.

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)0.006
metaresearch head score (Gemma)0.011
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 score0.006
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.019
Scholarly communication0.0060.012
Open science0.0010.006
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0040.000

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 head0.059
GPT teacher head0.320
Teacher spread0.260 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

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