An Empirical Research on the Relationship Between Firm Ownership Structure and Technical Innovation: Taking Manager Features as Mediums1 UNE RECHERCHE EMPIRIQUE SUR LA RELATION ENTRE
Bibliographic record
Abstract
The empirical research on the relationship between firm ownership structure and technical innovation is weak in existing research. Based on existing research result, this article empirically studies the influence of manager on relationship between firm ownership structure and technical innovation, by analysing a large sample database. It proves that firm manager is the important link between firm ownership structure and technical innovation. Keywords: ownership structure; attitude of manager; talent of manager; firm technical innovation Resume: La recherche empirique sur la relation entre la structure de propriete d’entreprise et l’innovation technologique est faible dans les recherches existantes. Basee sur le resultat de recherches existantes, cette these fait une recherche empirique sur les influences des managers sur la relation entre la structure proprietaires d’entreprises et l’innovation technologique en analysant une donnee exemplaire immense. Elle prouve que les managers des entreprises sont les liaisons importantes entre la structure de propriete d’entreprise et l’innovation technologique. Mots-cles: Structure proprietaire, attitudes des managers, talents des managers, l’innovation des entreprises technologiques
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".