Paper by Jen Nelles & David A. Wolfe: “This article argues that the concept of civic capital affords considerable insight into systems of urban economic development, usefully bridging gaps in both institution-centric and social capital approaches. While the concept has been applied in the literature on urban governance and economic development, its use has been fragmentary and has not seen broad engagement. This review of the state of the literature situates the concept of civic capital relative to existing literature in the field, highlights its relationship to other concepts, and reviews several qualitative approaches that apply the concept to case studies. It provides an overview of the concept and a description of the way it has developed alongside the rich literature on governance and social capital in urban development to illustrate its potential for further analytical study….(More)”.
Meaningful public engagement in the context of open science: reflections from early and mid-career academics
Paper by Wouter Boon et al: “How is public engagement perceived to contribute to open science? This commentary highlights common reflections on this question from interviews with 12 public engagement fellows in Utrecht University’s Open Science Programme in the Netherlands. We identify four reasons why public engagement is an essential enabler of open science. Interaction between academics and society can: (1) better align science with the needs of society; (2) secure a relationship of trust between science and society; (3) increase the quality and impact of science; and (4) support the impact of open access and FAIR data practices (data which meet principles of findability, accessibility, interoperability and reusability). To be successful and sustainable, such public engagement requires support in skills training and a form of institutionalisation in a university-wide system, but, most of all, the fellows express the importance of a formal and informal recognition and rewards system. Our findings suggest that in order to make public engagement an integral part of open science, universities should invest in institutional support, create awareness, and stimulate dialogue among staff members on how to ‘do’ good public engagement….(More)”.
A systematic review of worldwide causal and correlational evidence on digital media and democracy
Paper by Philipp Lorenz-Spreen, Lisa Oswald, Stephan Lewandowsky & Ralph Hertwig: “One of today’s most controversial and consequential issues is whether the global uptake of digital media is causally related to a decline in democracy. We conducted a systematic review of causal and correlational evidence (N = 496 articles) on the link between digital media use and different political variables. Some associations, such as increasing political participation and information consumption, are likely to be beneficial for democracy and were often observed in autocracies and emerging democracies. Other associations, such as declining political trust, increasing populism and growing polarization, are likely to be detrimental to democracy and were more pronounced in established democracies. While the impact of digital media on political systems depends on the specific variable and system in question, several variables show clear directions of associations. The evidence calls for research efforts and vigilance by governments and civil societies to better understand, design and regulate the interplay of digital media and democracy….(More)”
The Use of Data Science in a National Statistical Office
Paper by Sevgui Erman, Eric Rancourt, Yanick Beaucage, and Andre Loranger: “Objective statistical information is vital to an open and democratic society. It provides a solid foundation so that informed decisions can be made by our elected representatives, businesses, unions, and non-profit organizations, as well as individual citizens. There is a great shift towards a more virtual and digital economy and society. The traditional official statistical systems are centered on surveys, and must be adapted to this new digital reality. National statistical offices have been increasingly embracing non-survey data sources along with data science methods to better serve society.
This paper provides a blueprint for the application of data science in a government organization. It describes how data science enables innovation and the delivery of new high-value, high-quality, relevant, and trusted products that reflect the ever-evolving needs of our society and economy. We discuss practical operational considerations and impactful data science applications that supported the work of Statistics Canada’s analysts and front-line health agencies during the pandemic. We also discuss the innovative use of scanner data in lieu of survey data for large business respondents in the retail industry. We will describe computer vision methodologies, including machine learning models used to detect the start of buildings construction from satellite imagery, greenhouse area and greenhouse production, as well as crop types detection. Data science and machine learning methods have tremendous potential, and their ethical use is of primary importance. We conclude the paper with a forward-facing view of responsible data science use in statistical production.
Democracy by Design: Perspectives for Digitally Assisted, Participatory Upgrades of Society
Paper by Dirk Helbing et al: “The technological revolution, particularly the availability of more data and more powerful computational tools, has led to the emergence of a new scientific area called Computational Diplomacy. Our work focuses on a popular subarea of it. In recent years, there has been a surge of interest in using digital technologies to promote more participatory forms of democracy. While there are numerous potential benefits to using digital tools to enhance democracy, significant challenges must be addressed. It is essential to ensure that digital technologies are used in an accessible, equitable, and fair manner rather than reinforcing existing power imbalances. This paper investigates how digital tools can be used to help design more democratic societies by investigating three key research areas: (1) the role of digital technologies in facilitating civic engagement in collective decision-making; (2) the use of digital tools to improve transparency and accountability in gover-nance; and (3) the potential for digital technologies to enable the formation of more inclusive and representative democracies. We argue that more research on how digital technologies can be used to support democracy upgrade is needed, and we make some recommendations for future research in this direction…(More)”.
Artificial intelligence in government: Concepts, standards, and a unified framework
Paper by Vincent J. Straub, Deborah Morgan, Jonathan Bright, Helen Margetts: “Recent advances in artificial intelligence (AI) and machine learning (ML) hold the promise of improving government. Given the advanced capabilities of AI applications, it is critical that these are embedded using standard operational procedures, clear epistemic criteria, and behave in alignment with the normative expectations of society. Scholars in multiple domains have subsequently begun to conceptualize the different forms that AI systems may take, highlighting both their potential benefits and pitfalls. However, the literature remains fragmented, with researchers in social science disciplines like public administration and political science, and the fast-moving fields of AI, ML, and robotics, all developing concepts in relative isolation. Although there are calls to formalize the emerging study of AI in government, a balanced account that captures the full breadth of theoretical perspectives needed to understand the consequences of embedding AI into a public sector context is lacking. Here, we unify efforts across social and technical disciplines by using concept mapping to identify 107 different terms used in the multidisciplinary study of AI. We inductively sort these into three distinct semantic groups, which we label the (a) operational, (b) epistemic, and (c) normative domains. We then build on the results of this mapping exercise by proposing three new multifaceted concepts to study AI-based systems for government (AI-GOV) in an integrated, forward-looking way, which we call (1) operational fitness, (2) epistemic completeness, and (3) normative salience. Finally, we put these concepts to work by using them as dimensions in a conceptual typology of AI-GOV and connecting each with emerging AI technical measurement standards to encourage operationalization, foster cross-disciplinary dialogue, and stimulate debate among those aiming to reshape public administration with AI…(More)”.
Observing Many Researchers Using the Same Data and Hypothesis Reveals a Hidden Universe of Uncertainty
Paper by Nate Breznau et al: “This study explores how researchers’ analytical choices affect the reliability of scientific findings. Most discussions of reliability problems in science focus on systematic biases. We broaden the lens to include conscious and unconscious decisions that researchers make during data analysis and that may lead to diverging results. We coordinated 161 researchers in 73 research teams and observed their research decisions as they used the same data to independently test the same prominent social science hypothesis: that greater immigration reduces support for social policies among the public. In this typical case of research based on secondary data, we find that research teams reported widely diverging numerical findings and substantive conclusions despite identical start conditions. Researchers’ expertise, prior beliefs, and expectations barely predicted the wide variation in research outcomes. More than 90% of the total variance in numerical results remained unexplained even after accounting for research decisions identified via qualitative coding of each team’s workflow. This reveals a universe of uncertainty that is hidden when considering a single study in isolation. The idiosyncratic nature of how researchers’ results and conclusions varied is a new explanation for why many scientific hypotheses remain contested. It calls for greater humility and clarity in reporting scientific findings..(More)”.
Does South Africa’s Proposed State Ownership of Data Make Any Sense?
Paper by Enyinna S. Nwauche: “This paper interrogates the proposed state ownership of data by South Africa’s Draft National Cloud and Data Policy 2021 and argues that the quest for state ownership is evidence of South Africa’s policy preference for the state custodianship of critical natural resources. The paper suggests that a preferred reading of the proposed state ownership is the affirmation of a regulatory space to address issues related to the digital economy. This paper further suggests that regulatory oversight is inconsistent with the proposed state ownership because of the multi-dimensional nature of data and the fact that data is constitutional property. Rather than seek state ownership of data, the paper examines how to strike a delicate balance between the rights of citizens over data, such as privacy and the data use by companies who are recognized by South African Law to be entitled to some protection of privacy; intellectual property rights and confidential information. The paper sketches a framework of the balance in data governance in South Africa by reviewing jurisprudence that enables South Africa assert appropriate regulatory oversight through laws policies and institutions that enhance her digital economy…(More)”.
Who rules the deliberative party? Examining the Agora case in Belgium
Paper by Nino Junius and Joke Matthieu: “In recent years, pessimism about plebiscitary intra-party democracy has been challenged by assembly-based models of intra-party democracy. However, research has yet to explore the emergence of new power dynamics in parties originating from the implementation of deliberative practices in their intra-party democracy. We investigate how deliberative democratization reshuffles power relations within political parties through a case study of Agora, an internally deliberative movement party in Belgium. Employing a process-tracing approach using original interview and participant observation data, we argue that while plebiscitary intra-party democracy shifts power towards passive members prone to elite domination, our case suggests that deliberative intra-party democracy shifts power towards active members that are more likely to be critical of elites…(More)”
Can Social Media Rhetoric Incite Hate Incidents? Evidence from Trump’s “Chinese Virus” Tweets
Paper by Andy Cao, Jason M. Lindo & Jiee Zhong: “We will investigate whether Donald Trump’s “Chinese Virus” tweets contributed to the rise of anti-Asian incidents. We find that the number of incidents spiked following Trump’s initial “Chinese Virus” tweets and the subsequent dramatic rise in internet search activity for the phrase. Difference-in-differences and event-study analyses leveraging spatial variation indicate that this spike in anti-Asian incidents was significantly more pronounced in counties that supported Donald Trump in the 2016 presidential election relative to those that supported Hillary Clinton. We estimate that anti-Asian incidents spiked by 4000 percent in Trump-supporting counties, over and above the spike observed in Clinton-supporting counties…(More)”.