Stakeholder Dynamics and Performance Outcomes: Insights from UAE Medical Project Ecosystems
Notice bibliographique
Résumé
Bibliography Ahmed, R. a. (2017). Empirical study of project managers’ leadership competence and project performance. Engineering Management Journal, 29(3), pp.189-205. Ajmal, M. M. (2017). Factor analyzing project management practices in the United Arab Emirates. International Journal of Managing Projects in Business. Al-Ali, M. O. (2018). A 1000 Arab genome project to study the Emirati population. . Journal of human genetics, 63(4), 533-536. Antonacci, G. R. (2018). The use of process mapping in healthcare quality improvement projects. . Health services management research, , 31(2), pp.74-84. Assaad, E.-A. (2020). Predicting project performance in the construction industry . journal of construction engineering and managment. Bahadorestani, A. N. (2020). Planning for sustainable stakeholder engagement based on the assessment of conflicting interests in projects. . Journal of Cleaner Production, , 242, p.118402. De Gooyert, V. R. (2017). 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Stakeholder Managment. Vancouver, Canada. Xu, X. X. (2021). Stakeholders’ power over the impact issues of building energy performance gap: A two-mode social network analysis. Journal of Cleaner Production. Zawaya. (2021, June 23). PROJECTS: Top 5 healthcare projects in GCC amount to a $2.5bln spending spree. Retrieved from Zawaya: https://www.zawya.com/mena/en/projects/story/PROJECTS_Top_5_healthcare_projects_in_GCC_amount_to_a_25bln_spending_spree-ZAWYA20210623115149/
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».