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Record W4366809337 · doi:10.1353/rss.2017.0006

Russell’s Two Theories of Memory

2017· article· en· W4366809337 on OpenAlexvenueno aff
Iva Apostolova

Bibliographic record

VenueRussell the Journal of Bertrand Russell Studies · 2017
Typearticle
Languageen
FieldPsychology
TopicPhilosophy and Theoretical Science
Canadian institutionsnot available
Fundersnot available
KeywordsMonismEpistemologyPeriod (music)Focus (optics)Philosophy of mindPsychologyMetaphysicsPhilosophyAesthetics

Abstract

fetched live from OpenAlex

In this paper I examine Russell’s account of memory in both the acquaintance and the neutral monist periods, more specifically, the years from 1910 until 1927, with emphasis on The Problems of Philosophy, Theory of Knowledge, and The Analysis of Mind. I argue that memory is central for understanding how knowledge works, which is the main reason it remained in the focus of Russell’s analysis even after the gradual shift to neutral monism. I propose that memory played a not insignificant role in that shift. While this paper aims to show that Russell’s theory of memory in the acquaintance period faced serious difficulties—mainly related to the commitment to direct realism—I argue that there is a consistent similarity and continuity between the theory of memory in the acquaintance period and that in the neutral monist period. Russell considered a similar type of memory to be paradigmatic and epistemically primary in both periods—a consideration, dictated, no doubt, by his commitment to the principles of Occam’s razor and psychological plausibility.

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)0.004
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0020.020
Scholarly communication0.0060.013
Open science0.0030.004
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0070.001

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 head0.045
GPT teacher head0.359
Teacher spread0.314 · 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 designNot applicable
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
Published2017
Admission routes1
Has abstractyes

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