Strengthening public health education and humanitarian response through academic volunteerism
Notice bibliographique
Résumé
INTRODUCTION: Volunteers are an integral part of the International Red Cross and Red Crescent (RCRC) Movement, with over 16 million people actively contributing to humanitarian action worldwide. Academic volunteerism within the Movement includes contributions from students, volunteers and professionals from academic institutions who offer their time and expertise. In this study we aimed to understand the process of embedding academic volunteers in humanitarian organizations such as the Canadian Red Cross (CRC) and assess the impact of their activities within the realm of public health education. METHODS: We used a qualitative case study design with an instrumental approach. All documents related to academic volunteers within the CRC database from September 2018 to August 2023 were gathered and reviewed. Data related to the processes around engaging with volunteers, timelines, outcomes and feedback surveys from students and staff members were extracted and a content analysis was conducted. A return-on-investment analysis (ROI) was conducted to assess the financial impact of engaging academic volunteers. RESULTS: A total of 68 academic volunteers were engaged with CRC, including unpaid or partially paid master's students, doctoral and postdoctoral fellows, and student volunteers. The collaboration between CRC and academic volunteers contributed to educational enrichment, professional development, knowledge transfer, operational efficiency, and talent pool expansion. Results from a survey on academic volunteerism further highlighted benefits such as maintaining project schedules, promoting diversity, and amplifying the Movement's voice on important matters. The return on investment for unpaid academic volunteers and Masters students was 70%. A five-fold increase was measured for partially paid academic volunteers resulting in 486% ROI. DISCUSSION: Academic volunteerism yields mutual benefits for students, academic researchers, and humanitarian organizations. These volunteers enhance operational efficiency and fortify resilience, fostering adaptability amid challenges. They play a crucial role in strengthening evidence-based programming within organizations like CRC and bolstering their capacity to address emerging health issues. These volunteers constitute a valuable talent pool, bringing organizational knowledge and experience to the table. They provide critical support for scaling up programs, especially during emergency situations, offering innovative solutions to address human resource shortages driven by funding constraints.
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 | 0,002 | 0,010 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 ».