Conducting operational research in humanitarian settings: is there a shared path for humanitarians, national public health authorities and academics?
Notice bibliographique
Résumé
In humanitarian contexts, it is a difficult and multi-faceted task to enlist academics, humanitarian actors and health authorities in a collaborative research effort. The lack of research in such settings has been widely described in the past decade, but few have analysed the challenges in building strong and balanced research partnerships. The major issues include considering operational priorities, ethical imperatives and power differentials. This paper analyses in two steps a collaborative empirical endeavour to assess health service utilization by Syrian refugee and Lebanese women undertaken by the International Committee of the Red Cross (ICRC), the Lebanese Ministry of Public Health (MoPH) and the Harvard François-Xavier Bagnoud (FXB) Center. First, based on challenges documented in the literature, we shed light on how we negotiated appropriate research questions, methodologies, bias analyses, resource availability, population specificities, security, logistics, funding, ethical issues and organizational cultures throughout the partnership. Second, we describe how the negotiations required each partner to go outside their comfort zones. For the academics, the drivers to engage included the intellectual value of the collaboration, the readiness of the operational partners to conduct an empirical investigation and the possibility that such work might lead to a better understanding in public health terms of how the response met population needs. For actors responding to the humanitarian crisis (the ICRC and the MOPH), participating in a technical collaboration permitted methodological issues to be worked through in the context of deliberations within the wider epistemic community. We find that when they collaborate, academics, humanitarian actors and health authorities deploy their respective complementarities to build a more comprehensive approach. Barriers such as the lack of uptake of research results or weak links to the existing literature were overcome by giving space to define research questions and develop a longer-term collaboration involving individual and institutional learning. There is the need ahead of time to create balanced decision-making mechanisms, allow for relative financial autonomy, and define organizational responsibilities. Ultimately, mutual respect, trust and the recognition of each other's expertise formed the basis of an initiative that served to better understand populations affected by conflict and meet their needs.
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 | 0,007 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,005 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,002 |
| 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 ».