The number of scholars working on transition concepts in the Global South is rapidly increasing. In this context, a substantial amount of research output particularly focusses on niches and how they affect transition towards sustainability in a wider framework of the multi-level-perspective. At the same time, there is a growing interest in digital technology and its effect on sustainability challenges. In this article, we combine the two fields, and by utilizing social media data, we create an innovative network science approach to analyze the production environment of digital innovations in Africa. We focus on three innovation hubs that we conceptualize as niches and innovation intermediaries that not only create communities to develop, test and implement new technology but also function as networks to discuss and form new ideas around innovations. Our key findings show how local communities are embedded in larger innovation structures. The connections between local stakeholders and global actors are predominantly created through bridge actors, who hold key positions in their communities. With tools from network science, we demonstrate that these linking elements can regulate and steer discussions and therefore, strongly influence digital niche environments. Utilizing geographical location data, we can also see that the online space of technological innovations in Africa is heavily cantered in urban areas.
The increasing datafication of African societies has led to a proliferation of data science-related training opportunities. These trainings provide young people with the opportunity to learn the skills to work on Data science, with some focused specifically on women and girls. While this is encouraging and brings new opportunities for women and girls to participate in the knowledge economy, it is important to understand the wider context of data science training in Africa, in particular, how women and girls experience their (data science) education, and how this knowledge can impact their lives, sustain livelihoods and bring empowerment. Through a review of the literature, as well as an examination of different pedagogical approaches and practices used by various formal and informal training programs in Africa, we examined the experience of women and girls. We conducted a mapping of the training and networks that have been set up to provide knowledge and skills and to empower women in data science. We highlight some of the facilitators that have positively contributed to a greater participation of women and girls in data science education, while also revealing some of the barriers and structural impediments to fair access to training for women in data science.
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