Browsing by Author "Kabaseke, Clovis"

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    COVID 19: Lets act now: the urgent need for upscaling agroecology in Uganda (2020)
    (Taylor & Francis, 2020-11) Jumba, Francis Richard; Tibasiima, Tadeo; Byaruhanga, Eriah; Aijuka, Joshua; Pabst, Holger; Nakalanda, Julie Matovu; Kabaseke, Clovis
    ABSTRACT. The COVID 19 pandemic has ravaged most parts of the world leading to multiple negative effects as restrictions in movement have ensued. Uganda as a country has not been spared with such pandemics also known to disrupt food systems. The aim of this paper is to critically reflect and argue for alternative food systems in Uganda like agroecology that are deemed more resilient in times of pandemics like COVID19. We review and critically analyze the elements of agroecology in this respect and make strong recommendations for upscaling agroecology in Uganda.
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    Does the farmer’s social information network matter? Explaining adoption behavior for disaster risk 2 reduction measures using the theory of planned behavior
    (Theory of Planned Behavior, 2022) Mutyebere, Rodgers; Twongyirwe, Ronald; Sekajugo, John; Kabaseke, Clovis; Kagoro-Rugunda, Grace; Kervyn, Matthieu; Vranken, Liesbet
    Smallholder farmers’ vulnerability to climate-related disasters in Sub-Saharan Africa is increasing, partly due to land-use changes and limited information about the adoption of farm-based Disaster Risk Reduction (DRR) measures. Classical agricultural extension workers are increasingly less trusted because they tend to transfer information not targeted to DRR, and rarely reach remote areas vulnerable to disasters. By extending the Theory of Planned Behavior (TPB), this study assesses whether Social Information Networks (SIN) can shape farmers’ perspectives regarding the adoption of DRR measures. Cross-sectional data were collected from 602 randomly selected households from Rwenzori and Ankole in Western Uganda, the sub-regions that are prone to landslides and floods. Results from the structural equation modeling demonstrate TPB as a strong framework to explain adoption behavior for DRR measures. Results show Perceived Behavioral Control (PBC) as a stronger driver of intentions than subjective norm and attitudes. Intentions to apply DRR measures are significantly associated with actual adoption. Farmers’ adoption behavior to control landslides and floods is directly correlated since the same location might simultaneously be at risk of such interacting disasters. Furthermore, SIN significantly predicts adoption intentions directly, and indirectly through PBC, subjective norm, and attitude. PBC and professional networks being the main drivers of adoption intentions suggests that the role of extension services cannot be substituted by informal social networks but the two should be complementary. Thus, the study shows the need to build the technical capacity of extension staff and informal networks in DRR measures to train and transfer information to farmers.