L’équilibre ponctué et les leviers du changement en continu
Bibliographic record
Abstract
Cette recherche de nature qualitative et inductive, sous forme d’étude de cas, apporte un éclairage sur l’alternance entre les changements organisationnels en rupture et ceux en continu, ainsi que sur la conduite de ces derniers. Premièrement, l’analyse des pratiques déployées par l’entreprise à l’étude pour relier les deux types de changements et stimuler celui en continu indique qu’il est possible de retarder efficacement un nouveau changement en rupture, et d’ainsi influencer « l’équilibre ponctué ». Deuxièmement, l’analyse de ce cas et des écrits recensés inspire un modèle selon lequel les pratiques déployées pour impulser le changement en continu peuvent s’articuler pour créer des capacités dont les extrants, tel le réinvestissement des leçons tirées de l’expérience, représentent des leviers qui entretiennent ce changement en continu.
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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 | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.011 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".