Suchergebnisse

This report highlights the experiences of one of Myanmar's leading research organizations in compiling, analyzing, and publishing political data for local audiences on an online information platform (called MyPILAR). The development of this digital information platform from January to June of 2016 fostered better collaboration and provided first-hand experience in learning how to work with and manage databases; however, it also alluded to the limitations that organizations face amidst Myanmar's current data culture. In subsequently conducting a needs assessment among other government and civil society organizations that collect and use data for decision marking to learn how they collaborate, identify distribution and utilization paths, and process data, the Enlightened Myanmar Research Foundation (EMReF) discovered that these institutions have faced similar experiences in navigating a muddled and complex information environment and data culture. EMReF, one of two local organizations collaborating with the University of Washington, the Tableau Foundation, and the United States Agency for International Development (USAID) to improve data literacy and data strategies for evidence-based decision making in Myanmar, identified and addressed data management, production, curation, analysis, and sharing practices while launching the MyPILAR information platform and conducting an assessment among prospective members for a cohort to collectively address gaps in the emerging environment and improve good data practices across individuals and organizations partaking in Myanmar's data ecosystem. Members included government ministries, civil society organizations, and the media. EMReF selected those interviewed by their important role in collecting, sharing, or using data for public purposes or by their willingness to participate. Through EMReF's experience, this report documents two important and interconnected situations: 1) it sheds light on the array of data culture practices and situations contributing to Myanmar's data environment, and 2) it provides details on how one organization, in working within this environment, learned to identify these practices and overcome obstacles in producing high quality and accessible data for the public.

AbstractIn the United States (US), children's 'best interest' principles are central to child welfare policy, but their incorporation into immigration laws is less robust. Drawing on data from international and domestic policies, interviews with legal professionals and legal guidelines, we compare how Special Immigrant Juvenile Status (SIJS) and asylum – the main forms of immigration relief for undocumented youths in the US – align with children's best interest principles. SIJS, while promising, undermines family integrity by imposing rigid child‐rearing standards that may penalize immigrant families. Asylum upholds family integrity, but the application process involves intense interviews and strict evidentiary standards that harm youths' well‐being. Given asylum's high denial rates, the process often results in trauma without much promise of the permanency asylum can offer. Consequently, both SIJS and asylum fall short of protecting children's rights and best interests. We argue that how legal systems manage youths significantly affects youths' well‐being and their access to rights and benefits. The impact of legal processes on youths should be paramount to best interest policies and practices. We conclude with policy recommendations for SIJS and asylum that better promote children's best interests.

Purpose
The purpose of this paper is three-fold. Firstly, through selected case studies, to provide an overview of how non-traditional data from digital public services were used as a source of knowledge for policymaking. Secondly, to argue for a design for policy approach to support the successful integration of non-traditional data into policymaking practice, thus supporting data-driven innovation for policymaking. Thirdly, to encourage a vision of the relation between data-driven innovation and public policy that considers policymaking outside the authoritative instrumental logic perspective.


Design/methodology/approach
A qualitative small-N case study analysis based on desk research data was developed to provide an overview of how data-centric public services could become a source of knowledge for policymaking. The analysis was based on an original theoretical-conceptual framework that merges the policy cycle model and the policy capacity framework.


Findings
This paper identifies three potential areas of contribution of a design for policy approach in a scenario of data-driven innovation for policymaking practice: the development of sensemaking and prefiguring activities to shape a shared rationale behind intra-/inter-organisational data sharing and data collaboratives; the realisation of collaborative experimentations for enhancing the systemic policy analytical capacity of a governing body, e.g. by integrating non-traditional data into new and trusted indicators for policy evaluation; and service design as approach for data-centric public services that connects policy decisions to the socio-technical context in which data are collected.


Research limitations/implications
The small-N sample (four cases) selected is not representative of a broader population but isolates exemplary initiatives. Moreover, the analysis was based on secondary sources, limiting the assessment quality of the real use of non-traditional data for policymaking. This level of empirical understanding is considered sufficient for an explorative analysis that supports the original perspective proposed here. Future research will need to collect primary data about the potential and dynamics of how data from data-centric public services can inform policymaking and substantiate the proposed areas of a design for policy contribution with practical experimentations and cases.


Originality/value
This paper proposes a convergence, yet largely underexplored, between the two emerging perspectives on innovation in policymaking: data for policy and design for policy. This convergence helps to address the designing of data-driven innovations for policymaking, while considering pragmatic indications of socially acceptable practices in this space for practitioners.

How did instructors design their sociology courses for remote teaching during the 2020–2021 academic year, and what challenges did they face in teaching those courses? To answer these questions, we surveyed lead instructors and graduate teaching assistants (n = 77) in the Sociology Department at the University of Michigan, supplemented by interviews with students and our experiences as remote course consultants. Through this case study, we found that instructors cited increased workload and lack of connection as challenges with remote teaching, in addition to pandemic-related struggles. Most instructors reported using either synchronous or a mix of synchronous and asynchronous instruction in course design, incorporating both formative and summative assessments, and implementing communication and community-building strategies to establish connections with and among students. We argue that these challenges and course designs highlight the importance of care-informed pedagogy to not only remote teaching in 2020–2021 but also sociology instruction in general.