Demographic Influences on Indigenous Knowledge Practices in Chief Albert Luthuli Municipality
Journal Title: Acadlore Transactions on Applied Mathematics and Statistics - Year 2023, Vol 1, Issue 2
Abstract
In recent years, a surge in studies concerning indigenous knowledge (IK) has been observed, yet a clear definition of IK remains elusive. Discrepancies in international studies lead to fluid interpretations of the concept. The present study seeks to delineate the key elements characterizing knowledge as either indigenous or foreign to a specific community. Through a meticulous exploration of definitions surrounding indigenous knowledge, it is posited that all knowledge forms can be considered indigenous within the communities of their origination. To elucidate this argument, the impact of community demographics on the adoption of knowledge perceived as indigenous within the Chief Albert Luthuli Municipality was investigated. Data were collected using structured interviews, involving a total of 398 respondents. Analyses were conducted employing a mixed-method approach, utilizing Microsoft Excel and the Statistical Package for Social Sciences (SPSS). Findings revealed a significant relationship between variables such as commonly spoken language, cultural attributes, age, and employment level with IK practices within communities. Furthermore, the economic factors, including employment status, education levels, and household income, were examined for their association with the adoption of IK practices. It was discerned that such variables were correlated with the adoption of IK practices, especially as alternative strategies in the absence of consistent household income. Key determinants like the language proficiency of the household head, employment status, educational attainment, family size, household income level, age, and gender of the household heads were analyzed. The influence of these determinants on household adoption of indigenous practices was assessed using inferential statistical methods, specifically probability and regression analysis.
Authors and Affiliations
Matlhodi Famo, Machate Machate
Keywords
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- EP ID EP732901
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