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L’économie post-keynésienne, une pensée hétérodoxe méconnue ?

2022· article· fr· W4283762643 on OpenAlexaffvenueabout
Marc Lavoie, Mario Seccareccia

Bibliographic record

VenueInterventions économiques · 2022
Typearticle
Languagefr
FieldEconomics, Econometrics and Finance
TopicEconomic Theory and Policy
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsHumanitiesPhilosophyArt

Abstract

fetched live from OpenAlex

L’article se penche sur la théorie post-keynésienne, qui est l’une des écoles de pensée hétérodoxes en économie. Nous évoquons tout d’abord les principales caractéristiques des écoles de pensée hétérodoxes en général, puis les caractéristiques spécifiques à l’économie post-keynésienne. Nous identifions ensuite six domaines où l’on peut affirmer que la théorie post-keynésienne a eu un impact au cours de la dernière décennie. Nous tentons ensuite de tracer un bref portrait historique de la présence de la théorie post-keynésienne au Québec et accessoirement au Canada. Nous nous penchons plus particulièrement sur un ouvrage de 1954 de Maurice Lamontagne, un ancien enseignant à l’Université Laval et un ancien ministre fédéral. Cet ouvrage encore aujourd’hui suscite l’étonnement, car certains de ses passages auraient pu être écrits par des auteurs post-keynésiens contemporains. Nous montrons aussi le rôle fondamental joué par le département de science économique de l’Université McGill dans la diffusion de la pensée post-keynésienne au Québec et aussi en Ontario.

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)0.003
metaresearch head score (Gemma)0.006
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: Other · Consensus signal: Other
Teacher disagreement score0.242
Threshold uncertainty score0.482

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0050.028
Scholarly communication0.0110.011
Open science0.0010.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0120.001

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 head0.057
GPT teacher head0.273
Teacher spread0.216 · 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
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

Citations2
Published2022
Admission routes3
Has abstractyes

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