Factors Influencing Change of Smallholder Organic Horticultural Farmer Organisations under Nongovernmental Organisations in Two Selected Regions in Tanzania
Notice bibliographique
Résumé
There has been the persistent failure of organic horticultural production to meet its full potential in various aspects including productivity, technological and marketing areas in various Sub Saharan countries in Africa including Tanzania. Thus, this study intended to determine whether a change of Smallholder Organic Horticultural Farmer Organisations (SOHFOs) under the local umbrella Non-governmental Organisations (NGOs)with the mandate to work within the country in coordinating SOHFOs is influenced by relational factors (their networks with other Organic Horticultural Value Chain Actors (OHVCAs)) or non-relational (other) factors. The study was conducted in Morogoro and Kilimanjaro regions in Tanzania. A study included a total of one hundred fifty nine organizations (159) that were represented with three hundred fifty one (351) respondents. From one hundred and forty nine (149) SOHFOs under local umbrella NGOs selected by simple random sampling technique and further proportionate random sampling, quantitative data were collected from two hundred and eighty nine (289) respondents and qualitative data were collected from forty four (44) SOHFOs participants. Moreover, from ten (10) managing organisations represented by eighteen (18) Key Informants qualitative data were collected. Quantitative data (relational data) were analysed using the social network analysis approach using Ghephi 0.9.2 software. For non-relational data, Statistical Packages for Social Science (SPSS) version 21 was used whereby descriptive statistics such as measures of centralities (that is closeness centralities (CCs) and betweenness centralities (BCs)) and mean scores were used to establish some of the variables of the study. Binary logistic regression model was used to predict the factors influencing change (which is regarded as use of manure) at SOHFOs under local umbrella NGOs. Qualitative data were analysed using content analysis. Results from binary logistic regression model and content analysis indicate that SOHFOs under local umbrella NGOs are experiencing change in technological area whereby, soil erosion control measures are the most used technological practice as opposed to the use of organic manure. Again, the results on predictor factors for use of manure at SOHFOs under local umbrella NGOs indicate that relational factors; that is capacity of SOHFO to access and disseminate knowledge and information to other SOHFOs and to access and spread organic horticultural products and farm inputs to other OHVCAs are the significant factors over individual organisational attribute of SOHFOs under the local umbrella NGOs in Tanzania. The study recommends policies and systems that put emphasis on relational measures for more effective organic horticultural agriculture via SOHFOs under the local umbrella NGOs in Tanzania.
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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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,004 |
| 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 ».