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Vitalis Basera
Manicaland State University of Applied Sciences, Mutare, Zimbabwe
Religion Humanities Education Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Social Sciences

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Modelling association between two Multiple Response Categorical Variables (MRCV) using generalized log-linear models: the case of urban agriculture in Mutare City Absai Chakaipa; Vitalis Basera; Phamella Dube
Journal of Social, Humanity, and Education Vol. 1 No. 2 (2021): February
Publisher : Goodwood Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35912/jshe.v1i2.401

Abstract

Purpose: This research aimed to apply log-linear modelling to model association between multiple response categorical variables (MRCV) on urban agriculture and enhance data analysis of the paper by Basera, Chakaipa, & Dube (2020) impetus of urban agriculture on open spaces of Mutare City. Research methodology: The research data was obtained from households and farmers in Mutare City - urban and peri-urban (inclusive of plots in Weirmouth Park and Fern Valley area in December 2020. A total of one hundred and fifteen (115) household farmers were surveyed. Results: Simultaneous Pairwise Marginal Independence (SPMI) tests revealed the presence of associations. Log-linear tests revealed a perfect fit based on small standardized Pearson residuals and a strong positive association based on observed and model-predicted odds ratios on-field agricultural activities and use of herbicides. Log-linear and further application of heterogeneity tests revealed partial and near no perfect fit in other pairs of MRCVs with a strong negative association between municipality vacant places and field agricultural activities. Limitations: The research could not carry out log-linear model associations of three or more MRCVs because files exceeded 2GB in memory on both MI.test () function for SPMI tests and genloglin regressions. Contribution: The study contributes to urban agriculture planning especially in enactment of urban agriculture laws, agriculture one stop shop business centers housing farm input supply shops, farm produce shops, and determining fit support that can be rendered to urban farmers. Keywords: Multiple Response Categorical Variables (MRCV), Association, Urban agriculture
Modelling association between two Multiple Response Categorical Variables (MRCV) using generalized log-linear models: the case of urban agriculture in Mutare City Absai Chakaipa; Vitalis Basera; Phamella Dube
Journal of Social, Humanity, and Education Vol. 1 No. 2 (2021): February
Publisher : Goodwood Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35912/jshe.v1i2.401

Abstract

Purpose: This research aimed to apply log-linear modelling to model association between multiple response categorical variables (MRCV) on urban agriculture and enhance data analysis of the paper by Basera, Chakaipa, & Dube (2020) impetus of urban agriculture on open spaces of Mutare City. Research methodology: The research data was obtained from households and farmers in Mutare City - urban and peri-urban (inclusive of plots in Weirmouth Park and Fern Valley area in December 2020. A total of one hundred and fifteen (115) household farmers were surveyed. Results: Simultaneous Pairwise Marginal Independence (SPMI) tests revealed the presence of associations. Log-linear tests revealed a perfect fit based on small standardized Pearson residuals and a strong positive association based on observed and model-predicted odds ratios on-field agricultural activities and use of herbicides. Log-linear and further application of heterogeneity tests revealed partial and near no perfect fit in other pairs of MRCVs with a strong negative association between municipality vacant places and field agricultural activities. Limitations: The research could not carry out log-linear model associations of three or more MRCVs because files exceeded 2GB in memory on both MI.test () function for SPMI tests and genloglin regressions. Contribution: The study contributes to urban agriculture planning especially in enactment of urban agriculture laws, agriculture one stop shop business centers housing farm input supply shops, farm produce shops, and determining fit support that can be rendered to urban farmers. Keywords: Multiple Response Categorical Variables (MRCV), Association, Urban agriculture
Factors influencing student enrolment in young universities: A case study in Zimbabwe Vitalis Basera; Simbabrashe Munikwa
Journal of Social, Humanity, and Education Vol. 5 No. 4 (2025): August
Publisher : Goodwood Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35912/jshe.v5i4.2520

Abstract

Purpose: This study explored factors affecting students’ enrolment in young universities, focusing particularly on one young university in Zimbabwe. Young universities are experiencing enrolment challenges, which involve investigating the causal factors for sustainable development and operations of the universities. Research methodology: The study adopted the interpretivist paradigm and used a combination of qualitative approaches for data collection and analysis within a case study design. The study’s sample comprised ten heads of department, one admissions registrar and forty-eight students purposively selected from a young university. In-depth interviews and focus group discussions were used to generate the data. The data were analyzed using a directed content analysis approach. Results: The study revealed that students’ university enrolment is affected mainly by students’ experiences, career orientations, changes in high school graduate preferences, admissions process, transport, accommodation, programmes offered, competition in university education, social capital variables, government policy, cost of education, and disasters. Conclusions: The revealed key stakeholders influencing students’ enrolment in young universities reflected strategies that can be used to increase students’ enrolment, chiefly public awareness, academic support, and student support services. Limitations: While this study adopted a qualitative methodology, which can be a limiting factor in terms of inference, for further research, the study recommends the adoption of a quantitative method. Contribution: This study recommends that universities strategically plan for student enrolment using a multi-stakeholder approach. The study also recommends that the government adequately fund university development and ensure that university education is affordable to everyone.
Co-Authors Absai Chakaipa Phamella Dube Simbabrashe Munikwa