Paper by Daniel J. Benjamin, Kristen Cooper, Ori Heffetz & Miles S. Kimball: “Happiness data—survey respondents’ self-reported well-being (SWB)—have become increasingly common in economics research, with recent calls to use them in policymaking. Researchers have used SWB data in novel ways, for example to learn about welfare or preferences when choice data are unavailable or difficult to interpret. Focusing on leading examples of this pioneering research, the first part of this review uses a simple theoretical framework to reverse-engineer some of the crucial assumptions that underlie existing applications. The second part discusses evidence bearing on these assumptions and provides practical advice to the agencies and institutions that generate SWB data, the researchers who use them, and the policymakers who may use the resulting research. While we advocate creative uses of SWB data in economics, we caution that their use in policy will likely require both additional data collection and further research to better understand the data…(More)”.
Hopes over fears: Can democratic deliberation increase positive emotions concerning the future?
Paper by S. Ahvenharju, M. Minkkinen, and F. Lalot: “Deliberative mini-publics have often been considered to be a potential way to promote future-oriented thinking. Still, thinking about the future can be hard as it can evoke negative emotions such as stress and anxiety. This article establishes why a more positive outlook towards the future can benefit long-term decision-making. Then, it explores whether and to what extent deliberative mini-publics can facilitate thinking about the future by moderating negative emotions and encouraging positive emotions. We analyzed an online mini-public held in the region of Satakunta, Finland, organized to involve the public in the drafting process of a regional plan extending until the year 2050. In addition to the standard practices related to mini-publics, the Citizens’ Assembly included an imaginary time travel exercise, Future Design, carried out with half of the participants. Our analysis makes use of both survey and qualitative data. We found that democratic deliberation can promote positive emotions, like hopefulness and compassion, and lessen negative emotions, such as fear and confusion, related to the future. There were, however, differences in how emotions developed in the various small groups. Interviews with participants shed further light onto how participants felt during the event and how their sentiments concerning the future changed…(More)”.
Essential requirements for the governance and management of data trusts, data repositories, and other data collaborations
Paper by Alison Paprica et al: “Around the world, many organisations are working on ways to increase the use, sharing, and reuse of person-level data for research, evaluation, planning, and innovation while ensuring that data are secure and privacy is protected. As a contribution to broader efforts to improve data governance and management, in 2020 members of our team published 12 minimum specification essential requirements (min specs) to provide practical guidance for organisations establishing or operating data trusts and other forms of data infrastructure… We convened an international team, consisting mostly of participants from Canada and the United States of America, to test and refine the original 12 min specs. Twenty-three (23) data-focused organisations and initiatives recorded the various ways they address the min specs. Sub-teams analysed the results, used the findings to make improvements to the min specs, and identified materials to support organisations/initiatives in addressing the min specs.
Analyses and discussion led to an updated set of 15 min specs covering five categories: one min spec for Legal, five for Governance, four for Management, two for Data Users, and three for Stakeholder & Public Engagement. Multiple changes were made to make the min specs language more technically complete and precise. The updated set of 15 min specs has been integrated into a Canadian national standard that, to our knowledge, is the first to include requirements for public engagement and Indigenous Data Sovereignty…(More)”.
Data Repurposing through Compatibility: A Computational Perspective
Paper by Asia Biega: “Reuse of data in new contexts beyond the purposes for which it was originally collected has contributed to technological innovation and reducing the consent burden on data subjects. One of the legal mechanisms that makes such reuse possible is purpose compatibility assessment. In this paper, I offer an in-depth analysis of this mechanism through a computational lens. I moreover consider what should qualify as repurposing apart from using data for a completely new task, and argue that typical purpose formulations are an impediment to meaningful repurposing. Overall, the paper positions compatibility assessment as a constructive practice beyond an ineffective standard…(More)”
From Print to Pixels: The Changing Landscape of the Public Sphere in the Digital Age
Paper by Taha Yasseri: “This Mini Review explores the evolution of the public sphere in the digital age. The public sphere is a social space where individuals come together to exchange opinions, discuss public affairs, and engage in collective decision-making. It is considered a defining feature of modern democratic societies, allowing citizens to participate in public life and promoting transparency and accountability in the political process. This Mini Review discusses the changes and challenges faced by the public sphere in recent years, particularly with the advent of new communication technologies such as the Internet and social media. We highlight benefits such as a) increase in political participation, b) facilitation of collective action, c) real time spread of information, and d) democratization of information exchange; and harms such as a) increasing polarization of public discourse, b) the spread of misinformation, and c) the manipulation of public opinion by state and non-state actors. The discussion will conclude with an assessment of the digital age public sphere in established democracies like the US and the UK…(More)”.
Machine-assisted mixed methods: augmenting humanities and social sciences with artificial intelligence
Paper by Andres Karjus: “The increasing capacities of large language models (LLMs) present an unprecedented opportunity to scale up data analytics in the humanities and social sciences, augmenting and automating qualitative analytic tasks previously typically allocated to human labor. This contribution proposes a systematic mixed methods framework to harness qualitative analytic expertise, machine scalability, and rigorous quantification, with attention to transparency and replicability. 16 machine-assisted case studies are showcased as proof of concept. Tasks include linguistic and discourse analysis, lexical semantic change detection, interview analysis, historical event cause inference and text mining, detection of political stance, text and idea reuse, genre composition in literature and film; social network inference, automated lexicography, missing metadata augmentation, and multimodal visual cultural analytics. In contrast to the focus on English in the emerging LLM applicability literature, many examples here deal with scenarios involving smaller languages and historical texts prone to digitization distortions. In all but the most difficult tasks requiring expert knowledge, generative LLMs can demonstrably serve as viable research instruments. LLM (and human) annotations may contain errors and variation, but the agreement rate can and should be accounted for in subsequent statistical modeling; a bootstrapping approach is discussed. The replications among the case studies illustrate how tasks previously requiring potentially months of team effort and complex computational pipelines, can now be accomplished by an LLM-assisted scholar in a fraction of the time. Importantly, this approach is not intended to replace, but to augment researcher knowledge and skills. With these opportunities in sight, qualitative expertise and the ability to pose insightful questions have arguably never been more critical…(More)”.
On the culture of open access: the Sci-hub paradox
Paper by Abdelghani Maddi and David Sapinho: “Shadow libraries, also known as ”pirate libraries”, are online collections of copyrighted publications that have been made available for free without the permission of the copyright holders. They have gradually become key players of scientific knowledge dissemination, despite their illegality in most countries of the world. Many publishers and scientist-editors decry such libraries for their copyright infringement and loss of publication usage information, while some scholars and institutions support them, sometimes in a roundabout way, for their role in reducing inequalities of access to knowledge, particularly in low-income countries. Although there is a wealth of literature on shadow libraries, none of this have focused on its potential role in knowledge dissemination, through the open access movement. Here we analyze how shadow libraries can affect researchers’ citation practices, highlighting some counter-intuitive findings about their impact on the Open Access Citation Advantage (OACA). Based on a large randomized sample, this study first shows that OA publications, including those in fully OA journals, receive more citations than their subscription-based counterparts do. However, the OACA has slightly decreased over the seven last years. The introduction of a distinction between those accessible or not via the Scihub platform among subscription-based suggest that the generalization of its use cancels the positive effect of OA publishing. The results show that publications in fully OA journals are victims of the success of Sci-hub. Thus, paradoxically, although Sci-hub may seem to facilitate access to scientific knowledge, it negatively affects the OA movement as a whole, by reducing the comparative advantage of OA publications in terms of visibility for researchers. The democratization of the use of Sci-hub may therefore lead to a vicious cycle, hindering efforts to develop full OA strategies without proposing a credible and sustainable alternative model for the dissemination of scientific knowledge…(More)”.
Artificial Intelligence, Climate Change and Innovative Democratic Governance
Paper by Florian Cortez: “This policy-oriented article explores the sustainability dimension of digitalisation and artificial intelligence (AI). While AI can contribute to halting climate change via targeted applications in specific domains, AI technology in general could also have detrimental effects for climate policy goals. Moreover, digitalisation and AI can have an indirect effect on climate policy via their impact on political processes. It will be argued that, if certain conditions are fulfilled, AI-facilitated digital tools could help with setting up frameworks for bottom-up citizen participation that could generate the legitimacy and popular buy-in required for speedy transformations needed to reach net zero such as radically revamping the energy infrastructure among other crucial elements of the green transition. This could help with ameliorating a potential dilemma of voice versus speed regarding the green transition. The article will further address the nexus between digital applications such as AI and climate justice. Finally, the article will consider whether innovative governance methods could instil new dynamism into the multi-level global climate regime, such as by facilitating interlinkages and integration between different levels. Before implementing innovative governance arrangements, it is crucial to assess whether they do not exacerbate old or even generate new inequalities of access and participation…(More)”
Open Science and Data Protection: Engaging Scientific and Legal Contexts
Editorial Paper of Special Issue edited by Ludovica Paseri: “This paper analyses the relationship between open science policies and data protection. In order to tackle the research data paradox of the contemporary science, i.e., the tension between the pursuit of data-driven scientific research and the crisis of repeatability or reproducibility of science, a theoretical perspective suggests a potential convergence between open science and data protection. Both fields regard governance mechanisms that shall take into account the plurality of interests at stake. The aim is to shed light on the processing of personal data for scientific research purposes in the context of open science. The investigation supports a threefold need: that of broadening the legal debate; of expanding the territorial scope of the analysis, in addition to the extra-territoriality effects of the European Union’s law; and an interdisciplinary discussion. Based on these needs, four perspectives are then identified, that encompass the challenges related to data processing in the context of open science: (i) the contextual and epistemological perspectives; (ii) the legal coordination perspectives; (iii) the governance perspectives; and (iv) the technical perspectives…(More)”.
Surveys Provide Insight Into Three Factors That Encourage Open Data and Science
Article by Joshua Borycz, Alison Specht and Kevin Crowston: “Open Science is a game changer for researchers and the research community. The UNESCO Open Science recommendations in 2021 suggest that the practice of Open Science is a win-win for researchers as they gain from others’ work while making contributions, which in turn benefits the community, as transparency of conclusions and hence confidence in new knowledge improves.
Over a 10-year period Carol Tenopir of DataONE and her team conducted a global survey of scientists, managers and government workers involved in broad environmental science activities about their willingness to share data and their opinion of the resources available to do so (Tenopir et al., 2011, 2015, 2018, 2020). Comparing the responses over that time shows a general increase in the willingness to share data (and thus engage in open science).
A higher willingness to share data corresponded with a decrease in satisfaction with data sharing resources across nations.
The most surprising result was that a higher willingness to share data corresponded with a decrease in satisfaction with data sharing resources across nations (e.g., skills, tools, training) (Fig.1). That is, researchers who did not want to share data were satisfied with the available resources, and those that did want to share data were dissatisfied. Researchers appear to only discover that the tools are insufficient when they begin the hard work of engaging in open science practices. This indicates that a cultural shift in the attitudes of researchers needs to precede the development of support and tools for data management…(More)”.
