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Record W2111962360 · doi:10.7202/014921ar

Création et financement des entreprises technologiques : les leçons du modèle israélien

2007· article· fr· W2111962360 on OpenAlexaffvenueabout
Cécile Carpentier, Jean‐Marc Suret

Bibliographic record

VenueL Actualité économique · 2007
Typearticle
Languagefr
FieldBusiness, Management and Accounting
TopicPrivate Equity and Venture Capital
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsPolitical scienceHumanitiesArt

Abstract

fetched live from OpenAlex

Israël a développé, en quelques années, une industrie du capital de risque qui place ce pays parmi les premiers en termes de capital rapporté au produit intérieur brut. La stratégie d’intervention du gouvernement israélien ne se limite pas à l’offre de capital : axée vers la recherche, elle favorise la création d’entreprises technologiques. Elle comprend la mise en place d’incubateurs fortement arrimés aux universités et de programmes de formation de gestionnaires d’entreprises technologiques. L’octroi de subventions liées à des redevances est préféré aux mesures fiscales. Une action forte a donc été menée pour stimuler la demande de capital de risque. L’implication du gouvernement dans l’offre de capital a été temporaire, mais efficace. Au moyen de fonds mixtes, elle a permis, en 10 ans, le démarrage d’une industrie autonome, capable d’attirer des financements privés locaux et étrangers importants. Sous plusieurs aspects, le modèle israélien de développement du capital de risque diffère très largement de plusieurs initiatives d’autres juridictions. Son étude devrait guider la réflexion qui doit entourer la révision des programmes et organismes québécois.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.836
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.003
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.059
GPT teacher head0.249
Teacher spread0.190 · 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

Citations2
Published2007
Admission routes3
Has abstractyes

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