Social entrepreneurship as a tool for sustainable development in the townships in KwaZulu-Natal province
Bibliographic record
Abstract
Globally, social entrepreneurs have been identified as major contributors to solving social problems such as unemployment, poverty and inequality. They can also be considered a catalyst to economic transformation as a result of their significant contribution to a country’s Gross Domestic product (GDP) and have been identified as a crucial part of any country that aspires to achieve sustainable development. In countries, such as the United Kingdom, United States, Canada, France and Australia, growth in social value creation attributable to social entrepreneurs has strengthened, indicating any predicated or identified economic, social and environmental challenges may be mitigated or addressed by their inputs. This indicates beyond reasonable doubt that social entrepreneurs have an important role to play in any country and, it can also be argued, more especially in developing countries such as South Africa. The ineffective use and low contribution of this phenomenon to address the many socio-economic challenges affecting South Africa have been a significant concern to the South African government, academies, investors and policy makers, leading to a call for additional support for social entrepreneurship emergence and growth in the country. The National Development Plan (NDP) considers small businesses such as social enterprises a key component of any inclusive growth strategies and envisions by 2030, 90 percent of new jobs will be created by micro, small and medium enterprises. Research on factors affecting social entrepreneurs’ growth and their contribution to sustainable development in the country has seen various extensive studies in this field, nonetheless, a serious research gap remains regarding an in-depth understanding of those characteristics and factors that critically influence social entrepreneurship and improve their contribution to sustainable development. Furthermore, theoretical models of these factors are lacking. The current study, therefore, covers a critical research area with the potential to improve the present state of South African social entrepreneurship, with specific reference to social entrepreneurship within the townships in KwaZulu-Natal (KZN). The study aimed to identify the critical factors affecting social entrepreneurship as a tool for sustainable development in the KZN townships and to propose a prototype model to improve its effective contribution, since the contribution level currently experienced in the social sector is poor, which is attributed to various significant challenges faced by social entrepreneurs in South Africa. Research was thus conducted in three townships within the KZN Province, employing a quantitative research method, where the study population consisted of 90 social entrepreneurs. A non-probability, convenience sampling technique was adopted, while a closed-ended questionnaire was used to collect the primary data for the study. Inferential and descriptive statistical analysis of the data was undertaken using SPSS (version 27.0) software. The findings of the study indicate several challenges severely affect social entrepreneurs, who are constantly faced with significant barriers that affect their performance, impacting on social entrepreneurs’ innovativeness and creativity that could promote and improve their contribution to sustainable development. The study identified environmental factors to have a significant impact on social entrepreneurs’ contribution to sustainable development, while society’s perception, social networking, social impact measurement and access to financial resources were also identified as catalysts to social entrepreneurs’ performance. Key insights are provided into both the theoretical and practical implications of social entrepreneurs’ contribution to sustainable development. In addition, an extensive range of recommendations is outlined and a theoretical framework proposed for those factors that social entrepreneurs, government officials, and policy makers can understand to help develop remedies for current challenges affecting social entrepreneurs
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".