ABSTRACT
This research note explores the pressing ethical challenges associated with increased online platforming of sensitive research on conflict-affected settings since the onset of Covid-19. We argue that moving research online and the ‘digitalisation of suffering' risks reducing complexity of social phenomena and omission of important aspects of lived experiences of violence or peace-building. Immersion, ‘contexting' and trust-building are fundamental to research in repressive and/or conflict-affected settings and these are vitally eclipsed in online exchanges and platforms. ‘Distanced research' thus bears very real epistemological limitations. Neither proximity not distance are in themselves liberating vectors. Nonetheless, we consider the opportunities that distancing offers in terms of its decolonial potential, principally in giving local researcher affiliates' agency in the research process and building more equitable collaborations. This research note therefore aims to propose a series of questions and launch a debate amongst interested scholars, practitioners and other researchers working in qualitative research methods in the social sciences.
ABSTRACT
This qualitative study aimed to explore Singapore residents' knowledge, attitudes, perceptions, and behaviors around COVID-19 as shaped by different information sources. Through utilizing WhatsApp as a means of conducting digital focus group discussions (FGDs), participants were involved in five consecutive days of discussions through both synchronous and asynchronous means. We found that the use of WhatsApp as a means of conducting FGDs not only served as a means of generating essential, time-sensitive data in the community, but also advanced the quality and quantity of data generated, democratized, and enhanced the participatory nature of FGDs, and facilitated the communication of potential issues around data privacy between facilitators and participants. Although challenges around privacy and confidentiality remain, this means of collecting data is novel in terms of providing timely and relevant data during a pandemic and would be appropriate to be further utilized in the context of other health-related research beyond a public health emergency.
ABSTRACT
Food production systems face many challenges nowadays. Concerns regarding the environmental impact of increasingly intensive production, the rising cost of inputs needed to achieve adequate yields and the negative impact of the COVID-19 pandemic have put, and continuously put the agricultural sector in a difficult position regarding its sustainability, since even customers became conscious about them. Such external factors have affected both the animal production and the crop farming, inducing fundamental changes in these sectors, leading towards smart agriculture. Technology solutions have been increasingly experimented with and deployed to counterbalance the above. Currently, precision farming, and the use of so-called precision livestock technologies in large-scale livestock systems offer tangible, yet costly implementations to monitor and optimize yields. While pilot studies and prototypes have been widely demonstrated in the past 10 years, standard, scalable Internet of Things (IoT) based implementations are still lacking, mostly due to the complexity of the technology application. Many factors should be considered from communication protocol to protection against weather conditions to ensure that the employed IT solution can really add value to the livestock farmer at the end of the production cycle. This scoping review is focusing on the current good practices and challenges of the domain, and on appropriate data collection. Theoretical and practical factors that determine the quality of data collection and pre-processing are presented in this article, aiming to pave the road for future scalable precision livestock IoT implementation. © 2022 IEEE.