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Record W2115328574 · doi:10.1162/posc_a_00138

Explaining, Seeing, and Understanding in Thought Experiments

2014· article· en· W2115328574 on OpenAlexaff
James Robert Brown

Bibliographic record

VenuePerspectives on Science · 2014
Typearticle
Languageen
FieldArts and Humanities
TopicPhilosophy and History of Science
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsEpistemologyRelation (database)Thought experimentsortPhilosophyPsychologyComputer science

Abstract

fetched live from OpenAlex

In this paper, I analyze the relation between visualization and explanatory understanding in thought experiments. I discuss two thought experiments from special relativity. Both cases lead to a paradox, which can however be explained (away) as non-contradictory. The resolution in one of the two cases sheds light on the nature of thought experiments more generally by indicating what sort of thing it is that we see when we are observing events in the mind's own laboratory. And it will in turn shed light on the notions of explanation and understanding as they arise in thought experiments.

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)0.029
metaresearch head score (Gemma)0.059
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
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 score0.997
Threshold uncertainty score0.154

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0290.059
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0030.053
Scholarly communication0.0080.023
Open science0.0020.006
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0050.000

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 head0.111
GPT teacher head0.296
Teacher spread0.185 · 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.

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

Citations3
Published2014
Admission routes1
Has abstractyes

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