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Record W2128508057 · doi:10.7202/1008816ar

Le cyberentrepreneuriat : une étude exploratoire

2012· article· fr· W2128508057 on OpenAlexaffvenue
Camille Carrier, Louis Raymond, Anissa Eltaief

Bibliographic record

VenueRevue internationale P M E Économie et gestion de la petite et moyenne entreprise · 2012
Typearticle
Languagefr
FieldBusiness, Management and Accounting
TopicEntrepreneurship Studies and Influences
Canadian institutionsUniversité du Québec à Trois-Rivières
FundersCollege of Engineering, Michigan State UniversityMichigan State UniversityHarvard University
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

Les nouvelles technologies de l’information sont à l’origine d’une nouvelle forme d’entrepreneuriat, en l’occurrence le cyberentrepreneuriat, basée sur les nouveaux modèles d’affaires électroniques. Comme il s’agit d’un phénomène encore en phase d’émergence, il n’est pas étonnant de constater qu’il n’existe encore que très peu d’études sur le sujet ; la présente étude vise à combler cette lacune. Cette étude exploratoire en profondeur de cinq cas de cyberentreprises permet de jeter un éclairage sur le processus de création de la cyberentreprise ainsi que sur les stratégies et facteurs de compétitivité privilégiés par les cyberentrepreneurs concernés.

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)0.005
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.007
Science and technology studies0.0030.008
Scholarly communication0.0120.017
Open science0.0010.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0060.001

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 head0.020
GPT teacher head0.243
Teacher spread0.223 · 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 designQualitative
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

Citations5
Published2012
Admission routes2
Has abstractyes

Explore more

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