Microfinance and post-conflict reconstruction : organizational capacity-building of a CARE International microcredit project in Jaffna, Sri Lanka
Notice bibliographique
Résumé
The purpose of this thesis is to examine the challenges of capacity building of Community Based Organizations (CBO) in the microfinance sector, focused on poverty alleviation in Jaffna, Sri Lanka. This has been achieved by examining a case study of the pilot project, capacity building of CBOs in Jaffna (CAB-J project), being carried out by CARE International, Jaffna. For this purpose CARE has selected twenty CBOs to build their capacity in financial services to provide savings and credit services to vulnerable group of people. The ethnic conflict in Jaffna has caused massive destruction to the society, economy, public and private properties. Various subsidy and grants programs has developed a dependency syndrome among poor and they still remains as poor. They don't have adequate capital to invest in self employment activities. So there is an urgent need to build the local capacity in microfinance. The impact of the CAB-J microcredit program is analysed and discussed. Various challenges and implication of capacity building in microfinance in Jaffna post conflict context are also examined. A multiple method was used to collect necessary data and information including interviews, participatory observations, secondary data and comprehensive literature review regarding Jaffna context. The interviews primarily focused on the socio-economic impact of the project, various challenges and implications related to capacity building at institutional and grassroot level. The analysis was primarily based on the qualitative data. The study revealed that the CAB-J microcredit is an ideal tool in alleviating poverty in the post conflict context like Jaffna by strengthening the socio-economic structures of the Jaffna community rather than merely depend on grants or subsidy. But the actual impacts should be assessed in regards to the long term effect and sustainability of the program. But the project faced several challenges primarily lack of fund and human resources, high demand for non financial services, prevailing uncertain political situation, in building local capacity in microfinance. The study suggests that to achieve maximum outreach and sustainability some special components such as incorporating non financial services, blending the microcredit program with relief assistance, increasing human resources, and pouring more fund into the program should be incorporated into the existing programs
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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 | 0,000 | 0,000 |
| 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 ».