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Record W2103179823 · doi:10.1353/hms.2011.0295

Hume's Impression/Idea Distinction

2006· article· en· W2103179823 on OpenAlexvenueno aff
David Landy

Bibliographic record

VenueHume studies · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Economy and Marxism
Canadian institutionsnot available
Fundersnot available
KeywordsPhilosophyImpressionEpistemologyPsychologyComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

Understanding the distinction between impressions and ideas that Hume draws in the opening paragraphs of his A Treatise on Human Nature is essential for understanding much of Hume's philosophy. This, however, is a task that has been the cause of a good deal of controversy in the literature on Hume. I here argue that the significant philosophical and exegetical issues previous treatments of this distinction (such as the force and vivacity reading and the external-world reading) encounter are extremely problematic. I propose an alternative reading of this distinction as being between original mental entities and copied mental entities. I argue that Hume takes himself to discover this distinction as that which underlies our pre-theoretical sorting of mental entities. Thus, while the Copy Principle is initially treated by Hume as a mere empirical fact, it later comes to play a more substantial explanatory role in his account of human nature. This reading makes Hume's distinction a more philosophically robust one, and avoids many of the exegetical difficulties of previous interpretations.

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)0.003
metaresearch head score (Gemma)0.010
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: Other · Consensus signal: Other
Teacher disagreement score0.008
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.001
Science and technology studies0.0020.024
Scholarly communication0.0080.009
Open science0.0010.004
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0060.001

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 head0.048
GPT teacher head0.366
Teacher spread0.318 · 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
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

Citations33
Published2006
Admission routes1
Has abstractyes

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