Petites et moyennes entreprises à forte croissance et emploi dans le secteur manufacturier grec
Bibliographic record
Abstract
Cette étude a pour objet l’influence des PME à forte croissance sur la création d’emplois dans le secteur manufacturier grec. L’analyse empirique a été faite à partir de données provenant de recensements relevés au niveau d’établissements de plus de 20 salariés au cours de la période de cinq ans comprise entre 1992 et 1996. À partir de la croissance absolue, du taux de croissance et des indices de Birch et de Mustar, on a défini quatre groupes rassemblant les 10 % de PME qui se situent en tête pour la croissance. Les résultats des estimations réalisées par la méthode des probits indiquent que la taille de l’entreprise, les dépenses d’innovation, les exportations, la rentabilité, l’emplacement et la croissance du secteur agissent sur la probabilité d’appartenir aux quatre différents groupes de PME à forte croissance.
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 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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
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".