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Record W4411448495 · doi:10.1007/s11229-025-05103-6

Three arguments against metaphysical structuralism in consciousness research

2025· article· en· W4411448495 on OpenAlexfundno aff
Niccolò Negro

Bibliographic record

VenueSynthese · 2025
Typearticle
Languageen
FieldNeuroscience
TopicNeural dynamics and brain function
Canadian institutionsnot available
FundersAzrieli FoundationTel Aviv University
KeywordsStructuralism (philosophy of science)MetaphysicsConsciousnessEpistemologyPhilosophyPhilosophy of scienceCounterintuitiveSociology

Abstract

fetched live from OpenAlex

Abstract Phenomenal structuralism is the view that understanding consciousness requires describing its relational and structural properties, a perspective that can have implications for both explaining why experiences feel the way they do and identifying the neural correlates of consciousness. Phenomenal structuralism has gained considerable traction in recent years, with proponents advocating for its adoption as a new paradigm for consciousness science. This paper distinguishes three types of structuralism in consciousness studies: methodological, epistemological, and metaphysical. I critically evaluate metaphysical structuralism, which asserts that the phenomenal character of an experience is fully determined by its relational properties. I present three arguments challenging this metaphysical claim, demonstrating its inadequacy. I also claim, however, that this critique does not affect the fruitfulness of methodological and epistemological structuralism. This analysis clarifies the limits and prospects of the structuralist approach, emphasizing that methodological and epistemological structuralism can contribute to consciousness science without heavy and counterintuitive metaphysical commitments.

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)0.036
metaresearch head score (Gemma)0.058
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 score0.036
Threshold uncertainty score0.189

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0360.058
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.003
Science and technology studies0.0050.072
Scholarly communication0.0110.016
Open science0.0040.010
Research integrity0.0100.013
Insufficient payload (model declined to judge)0.0070.001

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 head0.061
GPT teacher head0.348
Teacher spread0.287 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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