Bibliographic record
Abstract
Cet article présente les résultats d’une analyse de l’ensemble des firmes de services aux entreprises françaises de plus de vingt salariés. L’originalité de l’approche vient de ce que chaque entreprise est analysée à l’aide de ses données comptables rassemblées par l’Enquête annuelle d’entreprises- services de l’INSEE. La méthodologie fait largement appel à l’analyse de données et, notamment, à l’analyse typologique. Les profils types relevés exploitent le fait que certaines attitudes stratégiques des firmes se traduisent, en fin de compte, par des résultats économiques et par des types d’organisation que l’on peut caractériser statistiquement. Deux types de résultats apparaissent dans l’article: l’analyse des profils apporte une connaissance plus riche et complémentaire à l’analyse traditionnelle par branche d’activité. En second lieu, les catégories repérées expriment bien l’existence de différenciations entre les firmes et, notamment, de caractères spécifiques au secteur des services aux entreprises.
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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".