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Record W6999512821

A Defense for Scientific Realism: Skepticisms, Unobservables & Interference to the Best Explanation

2017· other· en· W6999512821 on OpenAlexaff

Bibliographic record

VenueYorkSpace (York University) · 2017
Typeother
Languageen
Field
Topic
Canadian institutionsYork University
Fundersnot available
KeywordsSociology of scientific knowledgeInferencePhilosophy of scienceScientific reasoningBridging (networking)Work (physics)Empirical evidence
DOInot available

Abstract

fetched live from OpenAlex

The epistemological status of scientific knowledge claims has been undermined by skepticism, in particular by universal skepticism. This thesis asserts that Bas C. van Fraassens empirical stance is akin to universal skepticism. This work also maintains that van Fraassens empirical stance does not lead to the conclusion that scientific knowledge claims are empirically adequateespecially those claims that resulted from the scientific method of inference to the best explanation (IBE). To illustrate why van Fraassens stance does not devalue scientific knowledge claims will be suggested via Peter Liptons understanding of IBE combined with Ernan McMullins epistemic values. By bridging McMullins values with Liptons version of IBE, we get a more robust version of IBE; as a result, scientific claims may display a cluster of epistemic virtues and values. Where scientific knowledge claims display a cluster of epistemic virtues and values, they are simply beyond being empirically adequate.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.123
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0030.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.005

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 head0.082
GPT teacher head0.269
Teacher spread0.187 · 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 designNot applicable
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

Citations0
Published2017
Admission routes1
Has abstractyes

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