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Veblen, critique pionnier des « entreprises académiques »

2007· article· fr· W1912178149 on OpenAlexvenueno aff
Kenneth Bertrams

Bibliographic record

VenueInterventions économiques · 2007
Typearticle
Languagefr
FieldSocial Sciences
TopicInternational Science and Diplomacy
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

Depuis les années 1980, les universités européennes et nord-américaines ont accru leurs partenariats avec les entreprises privées afin de pallier la contraction des dépenses publiques consacrées à l’enseignement supérieur. Dans le chef de certains responsables universitaires, un comportement « entrepreneurial » a accompagné ces changements d’ordre budgétaire, assimilant volontiers les universités à de nouvelles entreprises de la connaissance. Le phénomène, cependant, n’avait rien de nouveau. Dès 1918, Veblen faisait paraître un livre interpellant sur cette question : The Higher Learning in America. A Memorandum on the Conduct of Universities by Business Men (Les études supérieures aux Etats-Unis. Un rapport sur la gestion des universités par les hommes d’affaires). Cet article retrace la genèse de la critique des « entreprises académiques » au sein de la pensée veblénienne de la science et de la technologie en la confrontant à ses propres contradictions. Au final, il souligne la portée et l’actualité des observations sociologiques de Veblen au regard des pressions exercées aujourd’hui sur les universités et la recherche scientifique fondamentale dans le cadre de la « société de la connaissance ».

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)0.004
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.043
Threshold uncertainty score0.086

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0090.020
Scholarly communication0.0090.010
Open science0.0010.004
Research integrity0.0060.009
Insufficient payload (model declined to judge)0.0070.002

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 head0.094
GPT teacher head0.431
Teacher spread0.336 · 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 designNot applicable
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
Published2007
Admission routes1
Has abstractyes

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