No abstract available.

Today, the District Health Information System 2 (DHIS2) has become the de-facto standard for open-source health management information systems and Sierra Leone's status as the first country in sub-Saharan Africa to implement DHIS2 makes it a productive place for researchers interested in understanding the end-to-end process of infrastructuring in a low-resource bureaucratic setting. In this article, we examine its design, implementation, and maintenance in Sierra Leone over a period of 14 years - from 2008 to 2022. We present an intensive case study discretized by three morphogenetic cycles (decentralization, centralization, and fragmentation) and furnished with explanatory account's of DHIS2's evolution using a critical realist research methodology to describe the emergence of DHIS2 as digital public health infrastructure. These accounts highlight the structural and cultural systems of DHIS2, their elaborations, and their interaction with agents over successive periods of DHIS2's evolution. Our study finds that, despite its continued use in Sierra Leone, the increasing generativity in the structural and cultural systems of DHSI2 and Sierra Leone's public health system engenders a persistent instability that requires continuous resolution. Though we find that extant literature aids in our understanding of DHIS2's evolution, we proffer two mechanisms, infrastructural capture and socio-technical debt, which aid our explanation of events observed in our case study. Our work makes a case for more ontologically-diverse theorizing of bureaucracy-aware computing systems.

Multilingual individuals code switch between languages as a part of a complex communication process.However, most computational studies have examined only one or a handful of contextual factors predictive of switching.Here, we examine Naijá-English code switching in a rich contextual environment to understand the social and topical factors eliciting a switch.We introduce a new corpus of 330K articles and accompanying 389K comments labeled for code switching behavior.In modeling whether a comment will switch, we show that topic-driven variation, tribal affiliation, emotional valence, and audience design all play complementary roles in behavior.