Tensions de gouvernance publique – une approche par les artéfacts de gestion
Bibliographic record
Abstract
Cet article vise à catégoriser des facteurs tensionnels en milieux organisationnels publics. Le contexte des réformes administratives engagées en Tunisie est saisi pour illustrer empiriquement des tensions de gouvernance publique (TGP) associées à des artéfacts de gestion. Trois types de facteurs sont isolés par l’étude. Leur analyse confirme des thèses de l’appropriation des outils de gestion et aident à améliorer la connaissance existante sur les processus d’atténuation des TGP en milieux organisationnels publics. Remarques à l’intention des praticiens La modernisation de la gouvernance publique est aujourd’hui synonyme d’introduction de nouveaux outils de management public en milieux administratifs. Sur le plan pratique, l’appropriation de ces outils génère des rapports tensionnels entre décideurs politiques et gestionnaires publics. Souvent perçues sous le prisme des injonctions paradoxales et des relations antagonistes qui perturbent le quotidien des organisations de l’État, les tensions de gouvernance publique sont gérables si on sait comment les identifier et catégoriser à partir des facteurs tensionnels associés aux réformes engagées.
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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 | 0.010 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.010 | 0.030 |
| Scholarly communication | 0.019 | 0.016 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".