MétaCan
Menu
Back to cohort
Record W2095787439 · doi:10.7202/602351ar

Les obstacles à l’innovation dans les industries de services au Canada

2009· article· fr· W2095787439 on OpenAlexaffvenueabout
Pierre Mohnen, Julio M. de la Rosa

Bibliographic record

VenueL Actualité économique · 2009
Typearticle
Languagefr
FieldEconomics, Econometrics and Finance
TopicFirm Innovation and Growth
Canadian institutionsCenter for Interuniversity Research and Analysis on OrganizationsUniversité du Québec à Montréal
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

De nombreux travaux se sont penchés sur les conditions qui favorisent les efforts en matière d’innovation technologique dans les entreprises canadiennes. L’objectif de cette étude est d’examiner l’innovation sous l’angle opposé, à savoir les obstacles perçus à l’innovation. Nous examinons les obstacles dans les industries des communications, de la finance et des services techniques. Les données proviennent de l’enquête innovation de 1996 menée par Statistique Canada. Premièrement, nous essayons de faire ressortir quelques facteurs expliquant la perception des obstacles à partir d’une analyse des données et d’un modèle économétrique. Deuxièmement, nous cherchons à déterminer dans quelle mesure certains obstacles sont complémentaires entre eux. Si complémentarité il y a, il faut adopter une approche systémique aux barrières à l’innovation pour y remédier efficacement.

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)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.062
Threshold uncertainty score0.452

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.008
Science and technology studies0.0050.002
Scholarly communication0.0060.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.053
GPT teacher head0.230
Teacher spread0.177 · 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 designObservational
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

Citations38
Published2009
Admission routes3
Has abstractyes

Explore more

Same venueL Actualité économiqueSame topicFirm Innovation and GrowthFrench-language works237,207