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Record W4399438140 · doi:10.1016/j.shpsa.2024.05.020

From the philosophy of measurement to the philosophy of classification: Generalizing the problem of coordination and historical coherentism

2024· article· en· W4399438140 on OpenAlexaff
François Papale

Bibliographic record

VenueStudies in History and Philosophy of Science Part A · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicPhilosophy and History of Science
Canadian institutionsUniversité LavalUniversité de Sherbrooke
Fundersnot available
KeywordsCoherentismPhilosophy of medicineEpistemologyPhilosophy of sciencePhilosophyAnalytic philosophyComputer scienceContemporary philosophyMedicineFoundationalism

Abstract

fetched live from OpenAlex

The objective of this paper is twofold. First, I present a framework called historical coherentism (Chang, 2004; Tal, 2016; Van fraassen 2008) and argue that it is the best epistemological framework available to tackle the problem of coordination, an epistemic conundrum that arises with every attempt to provide empirical content to scientific theories, models or statements. Second, I argue that the problem of coordination, which has so far been theorized only in the context of measurement practices (Reichenbach, 1927; Chang, 2001; Tal, 2012; Van fraassen 2008), can be generalized beyond the philosophy of measurement. Specifically, it will be shown that the problem is embodied in classificatory practices and that, consequently, historical coherentism is well suited to analyze these practices as well as metrological ones. As a case study, I look at a contemporary debate in phylogenetics, regarding the evolutionary origin of a newly identified archaeal phylum called Methanonatronarchaeia. Exploring this debate through the lens of historical coherentism provides a detailed understanding of the dynamics of the field and a foothold for critical analyses of the standard rationale used by practitioners.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.788
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.012
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.284
GPT teacher head0.296
Teacher spread0.011 · 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 teacher head, 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
Published2024
Admission routes1
Has abstractyes

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