Incidence de la loi proxémique sur la perception de l’incertitude des PME
Bibliographic record
Abstract
Les travaux concernant les PME suggèrent une spécificité induisant des modalités de gestion particulières des entreprises de petite dimension. Toutefois, sur quels ressorts repose cette spécificité ? La thèse défendue sera que la spécificité de la gestion des PME est la proximité. De nombreuses études ont démontré la préférence des PME, par l’intermédiaire de leur propriétaire-dirigeant, pour des relations de proximité. Nous chercherons à affiner cette vision en essayant de voir l’impact de cette proximité en ce qui concerne la perception d’incertitude de la part des PME. Sur la base d’une étude quantitative menée auprès de 239 PME et de tests statistiques à dimension exploratoire, nous essayerons d’appréhender deux propositions de recherche : la proximité est un réducteur d’incertitude et la proximité est un facteur de performance. Les résultats obtenus nous conduiront à envisager l’importance des relations de proximité.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 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".