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Record W3005563236 · doi:10.1522/revueot.v28n3.1080

L' entrepreneuriat technologique : ses parties prenantes et leurs implications

2020· article· fr· W3005563236 on OpenAlexaffvenueabout
Yan Castonguay, Samuel Saint-Yves, Rhizlane Hamouti, Alex Cayrol

Bibliographic record

VenueRevue Organisations & territoires · 2020
Typearticle
Languagefr
FieldBusiness, Management and Accounting
TopicPrivate Equity and Venture Capital
Canadian institutionsUniversité du Québec en OutaouaisUniversité du Québec à Rimouski
Fundersnot available
KeywordsPolitical scienceHumanitiesLibrary scienceArtComputer science

Abstract

fetched live from OpenAlex

Étant moins bien connu et documenté que l’entrepreneuriat conventionnel, l’entrepreneuriat technologique se distingue par son processus d’innovation gravitant principalement autour de la création d’une technologie. Ce projet de recherche vise à mieux comprendre le rôle des parties prenantes au sein de l’écosystème entrepreneurial lors de projets d’innovation technologique. Basées sur une approche exploratoire, 11 entrevues semi-structurées ont été réalisées en 2017 auprès d’entrepreneurs qui créent des technologies diverses dans la province de Québec au Canada. L’analyse de ces entrevues a permis d’identifier les implications des parties prenantes dans les trois phases du processus d’innovation technologique : la conception, la mise en oeuvre et le marketing. Par conséquent, cette recherche fournit non seulement des recommandations pour les entrepreneurs technologiques, mais aussi des pistes de recherche.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.813
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0000.000
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 head0.044
GPT teacher head0.241
Teacher spread0.198 · 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 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

Citations3
Published2020
Admission routes3
Has abstractyes

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