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Record W1591496887 · doi:10.1353/hms.2001.a383326

General Rules and the Justification of Probable Belief in Hume's Treatise

2001· article· en· W1591496887 on OpenAlexvenueno aff
Jack Lyons

Bibliographic record

VenueHume studies · 2001
Typearticle
Languageen
FieldArts and Humanities
TopicPhilosophical Ethics and Theory
Canadian institutionsnot available
Fundersnot available
KeywordsSuperstitionSkepticismPhilosophyEpistemologyDilemmaValue (mathematics)Face (sociological concept)TheologyMathematics

Abstract

fetched live from OpenAlex

By the conclusion of Book I of the Treatise, Hume faces something of a dilemma.Because of the skeptical arguments of part 4, he is "ready to reject all belief and reasoning, and can look upon no opinion even as more probable or likely than another" (T 268-9).*Yet on the other hand, he clearly does think that some methods of belief-formation are better than others.Five paragraphs after the passage just cited, he proclaims, "I make bold to recommend philosophy, and shall not scruple to give it the preference to superstition of every kind and denomination" (T 271).Although it is difficult to take much of what Hume says in part 4 (and especially section 7) at face value, it is clear that Hume is sincere in his endorsement of philosophy here.Book I, after all, is only the first of the three books of the Treatise, and the other two books begin just four (Selby-Bigge) pages after this endorsement.The skeptical ar- guments examined throughout the Treatise seem to indicate that we cannot show that many, if any, of our beliefs have a high probability of being true, and yet Hume wants to maintain a distinction between better and worse methods of belief-formation.On what could such a distinction be founded?Notoriously, there are several different themes in the Treatise that look like they might play some role; at various points in the Treatise, Hume mentions the involuntariness of belief, the pleasure derived from philosophy, the love of truth, the distinction between the more and less universal workings of the mind, and so forth.Not surprisingly, there is a good deal of debate among Hume's commentators as to which of these themes is actually at work ~ ~~~~~~~~

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)0.007
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 score0.007
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0030.019
Scholarly communication0.0050.007
Open science0.0010.002
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0030.001

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 head0.100
GPT teacher head0.298
Teacher spread0.198 · 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

Citations12
Published2001
Admission routes1
Has abstractyes

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