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Record W14813966 · doi:10.32920/22229269

The Problem of Observation

2003· article· en· W14813966 on OpenAlexaff
Avner Levin

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical Studies in Science
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsEpistemologyQuality (philosophy)Scientific lawBasis (linear algebra)LawTheoretical physicsSociologyPolitical sciencePhilosophyPhysicsMathematics

Abstract

fetched live from OpenAlex

An investigation of how law and science are similar. Against the background of proliferation of inquiries into the law of various aspects of science and technology it is worth noting that law and science share not only some interesting superficial analogies but also a deeper, common epistemological basis. More accurately, there are epistemological limits placed on both law and physics that are in all important respects similar. These limits on the 'quality' of knowledge imposed on both physicists and lawyers are known as a Problem of Observation existing in the disciplines of physics and law.

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)0.041
metaresearch head score (Gemma)0.118
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 score0.994
Threshold uncertainty score0.216

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0410.118
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0020.002
Science and technology studies0.0060.062
Scholarly communication0.0070.031
Open science0.0040.007
Research integrity0.0100.018
Insufficient payload (model declined to judge)0.0070.002

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 head0.075
GPT teacher head0.226
Teacher spread0.151 · 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

Citations0
Published2003
Admission routes1
Has abstractyes

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