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Record W6980773489

Conversation with Paul Dumouchel

2025· article· en· W6980773489 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicReligion and Society in Latin America
Canadian institutionsnot available
Fundersnot available
KeywordsConversationAmbivalencePoliticsIvory towerScarcityMoral philosophyAcademic freedom
DOInot available

Abstract

fetched live from OpenAlex

Paul Dumouchel is a Canadian philosopher, who worked as a professor at the Graduate School of Core Ethics and Frontier Sciences at Ritsumeikan University in Kyoto, Japan, where he taught political philosophy and the philosophy of science. Now based back in Canada, he is affiliated with the Department of Philosophy at the Université du Québec à Montréal (UQAM) and is a visiting researcher at the Centre de Recherche en Droit Public (CRDP) at the University of Montreal. Dumouchel served as President of the Canadian Philosophical Association and co-founded the Centre de Recherche en Épistémologie Appliquée (CREA) at the École Polytechnique in Paris. His published works include Emotions (1999), The Ambivalence of Scarcity and Other Essays (2014), and The Barren Sacrifice (2015). He co-edited Against Injustice: The New Economics of Amartya Sen (2009) and Social Bonds as Freedom (2015) with Reiko Gotoh, and his most recent book, Living with Robots (2017), was co-authored with Luisa Damiano. He has been visiting professor at the University of Cagliari since 2019, participating in the Visiting Professor/Scientist program, funded by Regional Law 7/2007 of the Autonomous Region of Sardinia. In this interview, he shares insights into his research, academic experiences, and the evolution of his philosophical thought.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.945
Threshold uncertainty score0.570

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 integrity0.0000.000
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 head0.008
GPT teacher head0.308
Teacher spread0.300 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2025
Admission routes1
Has abstractyes

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