MétaCan
Menu
Back to cohort
Record W3022412015

Money and Mental Contents

2019· article· en· W3022412015 on OpenAlexaff
Sarah Vooys, David G. Dick

Bibliographic record

VenuePhilSci-Archive (University of Pittsburgh) · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicPhilosophical Ethics and Theory
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsInstitutionPhenomenonPoint (geometry)Function (biology)Positive economicsEconomicsEpistemologySociologyPhilosophySocial scienceMathematics
DOInot available

Abstract

fetched live from OpenAlex

It can be hard to see where money fits in the world. Money seems both real and imaginary, since it has obvious causal powers, but is also, just as obviously, something humans have just made up. Recent philosophical accounts of money have declared it to be real, but for very different reasons. John Searle and Francesco Guala disagree over whether money is just whatever acts like money, or just whatever people believe to be money. In developing their accounts of institutions as a part of social reality, each uses money as a paradigm institution, but they disagree on how institutions exist. Searle argues that the institution of money belongs to an ontological level separate from the physical world, held up by the collective intentions of a group, while Guala claims that money is a part of the ordinary physical world and is just whatever performs a “money-like function” in a group, regardless of what that group believes about it. Here, we argue that any purely functional account like Guala’s will be unable to capture the distinctive phenomenon of money, since monetary transactions are defined by the attitudes transactors hold toward them. Money will be obscured or misidentified if defined functionally. As we go on to show by examining recent work by Smit et al., belief in money does not require taking on all of Searle’s ontological commitments, but money and mental contents will stand or fall together.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.213
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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.025
GPT teacher head0.192
Teacher spread0.168 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

Explore more

Same venuePhilSci-Archive (University of Pittsburgh)Same topicPhilosophical Ethics and TheoryFrench-language works237,207