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Record W4212931209 · doi:10.1111/meta.12542

Grounding interventionism: Conceptual and epistemological challenges

2022· article· en· W4212931209 on OpenAlexaff
Amanda Bryant

Bibliographic record

VenueMetaphilosophy · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicEpistemology, Ethics, and Metaphysics
Canadian institutionsToronto Metropolitan University
FundersFundação para a Ciência e a Tecnologia
KeywordsInterventionism (politics)EpistemologyCausationCounterfactual thinkingImpossibilityPhilosophyMetaphysicsGroundPolitical scienceLawInternational relationsPolitics

Abstract

fetched live from OpenAlex

Philosophers have recently highlighted substantial affinities between causation and grounding, which have inclined some to import the conceptual and formal resources of causal interventionism into the metaphysics of grounding. The prospect ofgrounding interventionismraises two important questions: What exactly are grounding interventions, and why should we think they enable knowledge of grounding? This paper approaches these questions by examining how causal interventionists have addressed (or might address) analogous questions and then comparing the available options for grounding interventionism. The paper argues that grounding interventions must be understood in worldly terms, as adding something to or deleting something from the roster of entities, or making some fact obtain or fail to obtain. It considers three bases for counterfactual assessment: imagination, structural equation models, and background theory. The paper concludes that grounding interventionism requires firmer epistemological foundations, without which the interventionist’s epistemology of grounding is incomplete and ineffectually rationalist.

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)0.066
metaresearch head score (Gemma)0.061
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.066
Threshold uncertainty score0.348

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0660.061
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0060.004
Science and technology studies0.0070.125
Scholarly communication0.0160.041
Open science0.0080.015
Research integrity0.0120.021
Insufficient payload (model declined to judge)0.0060.001

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 head0.206
GPT teacher head0.276
Teacher spread0.070 · 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 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

Citations2
Published2022
Admission routes1
Has abstractyes

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