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On Believing

2022· book· en· W4220957334 on OpenAlexaff
David Hunter

Bibliographic record

Venuenot available
Typebook
Languageen
FieldArts and Humanities
TopicEpistemology, Ethics, and Metaphysics
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsPsychologyPhilosophyEpistemology

Abstract

fetched live from OpenAlex

Abstract This book develops original accounts of the logical, psychological, and normative aspects of belief, grounded in ontological views that put the believer at the heart of the story. Hunter argues that to believe something is to be in position to do, think, and feel things in light of a possibility whose obtaining would make one right. The logical aspect is that being right depends only on whether that possibility obtains. The psychological one concerns how that possibility can rationalize what one does, thinks, and feels. But, Hunter argues, beliefs are not causes, capacities, or dispositions. Rather, believing rationalizes because possibilities are potential reasons. Hunter also denies that believing is a form of representing. The objects of belief are possibilities, not representations, and belief states are not themselves true or false. Hunter defends this modal view against familiar objections and explores how objective and subjective limits to belief generate credal illusions and ground credal necessities. Developing a novel account of the normativity of belief, he argues that voluntary acts of inference make us responsible for our beliefs. While denying that believing is intrinsically normative, Hunter grounds the ethics of belief in attributive goodness. Believing something is to our credit when it shows us to be good in some way, and what we ought to believe depends on what we ought to know, and not on the evidence we have. The ethics of belief, Hunter argues, concern how a believer ought to be positioned in a world of possibilities.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.378
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0650.001

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 head0.077
GPT teacher head0.256
Teacher spread0.180 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Citations18
Published2022
Admission routes1
Has abstractyes

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