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Record W4414086932 · doi:10.1080/09515089.2025.2556845

From monkeys to infants: the empirical challenges facing mental fictionalism

2025· article· en· W4414086932 on OpenAlexfundno aff
Gavin Robert Foster

Bibliographic record

VenuePhilosophical Psychology · 2025
Typearticle
Languageen
FieldPsychology
TopicChild and Animal Learning Development
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsEmpirical researchEmpirical evidenceMental modelCognition

Abstract

fetched live from OpenAlex

In recent decades, a novel theoretical account of folk psychology has emerged that challenges traditional assumptions: mental fictionalism. Rather than treating mental states as things in creatures’ minds that we are really tracking, mental fictionalists argue that folk psychology is best understood as a collective fiction that we partake in. On this account, it is this fiction rather than an ability to track mental states that enables us to predict/explain one another’s behavior, or to coordinate our affective states to grow and maintain social relationships. I provide an overview of the evidence from comparative and developmental psychology that is inconsistent with mental fictionalism, arguing that both views considered here are unable to account for the mindreading abilities of non-linguistic primates and children. I then offer an ontogenetic challenge, arguing that mental fictionalism faces the difficult task of explaining how mindreading could emerge from what are thought to be more sophisticated cognitive mechanisms, such as those underlying participation in either pretense or collective narratives. I conclude by highlighting the specific body of evidence that a more robust version of mental fictionalism should account for, especially as it continues to be refined and emerges as a serious competitor amongst interpretations of folk psychology.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.797
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.174
GPT teacher head0.432
Teacher spread0.258 · 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; both teacher heads agree on what is shown here.

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
Published2025
Admission routes1
Has abstractyes

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