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We examine deliberative quality of crowdsourced deliberation in this paper. Analyzing data from two crowdsourcedpolicy-making processes, we found a good quality deliberation with respect, reciprocity, and storytelling according tothe standards in the theory of deliberative democracy. We identified a group of super-deliberators, whose deliberationwas above the average, and low-quality deliberators, whose deliberation was below the average. The findings show that even when crowdsourced policymaking was not designed for deliberation, it can facilitate a fairly high-quality democratic deliberation.
In this paper, we examine the changes in motivation factors in crowdsourced policymaking. By drawing onlongitudinal data from a crowdsourced law reform, we show that people participated because they wanted toimprove the law, learn, and solve problems. When crowdsourcing reached a saturation point, the motivationfactors weakened and the crowd disengaged. Learning was the only factor that did not weaken. The participantslearned while interacting with others, and the more actively the participants commented, the more likelythey stayed engaged. Crowdsourced policymaking should thus be designed to support both epistemic andinteractive aspects. While the crowd's motives were rooted in self-interest, their knowledge perspectiveshowed common-good orientation, implying that rather than being dichotomous, motivation factors move ona continuum. The design of crowdsourced policymaking should support the dynamic nature of the processand the motivation factors driving it.
While national and local governments increasingly deploy crowdsourcing in lawmaking as an open government practice, it remains unclear how crowdsourcing creates value when it is applied in policymaking. Therefore, in this article, we examine value creation in crowdsourcing for public policymaking. We introduce a framework for analysing value creation in public policymaking in the following three dimensions: democratic, epistemic and economic. Democratic value is created by increasing transparency, accountability, inclusiveness and deliberation in crowdsourced policymaking. Epistemic value is developed when crowdsourcing serves as a knowledge search mechanism and a learning context. Economic value is created when crowdsourcing makes knowledge search in policymaking more efficient and enables government to produce policies that better address citizens' needs and societal issues. We show how these tenets of value creation are manifest in crowdsourced policymaking by drawing on instances of crowdsourcedlawmaking, and we also discuss the contingencies and challenges preventing value creation.
While crowdsourced democratic deliberation is becoming more common in open policymaking, it remains unclear what its value and role is — and should be, and could be — in policymaking. This paper examines crowdsourced democratic deliberation and its features, comparing it to the traditional mini-publics approach in democratic deliberation and to general online deliberation. The paper shows the promise of crowdsourced democratic deliberation as a method for scaling up deliberation to masses, while also illuminating its challenges, rooted in the self-selected and distributed nature of crowdsourcing. The paper concludes that the value of crowdsourced democratic deliberation remains mainly procedural rather than instrumental in policymaking.
This paper shows how the two virtues of collective intelligence – cognitive diversity and large crowds – turn into perils in crowdsourced policymaking. That is because of a conflict between the logic of the crowds and the logic of policymaking. The crowd's logic differs from that of traditional policymaking in several aspects. To mention some of those: In traditional policymaking it is a small group of experts making proposals to the policy, whereas in crowdsourced policymaking, it is a large, anonymous crowd with a mixed level of expertise. The crowd proposes atomicideas, whereas traditional policymaking is used to dealing with holistic and synthesized proposals. By drawing on data from a crowdsourced law-making process in Finland, the paper shows how the logics of the crowds and policymaking collide in practice. The conflict prevents policymaking fully benefiting from the crowd's input, and it also hinders governments from adopting crowdsourcing more widely as a practice for deploying open policymaking practices.
This paper examines the impact of crowdsourcing on a policymaking process by using a novel data analytics tool calledCivic CrowdAnalytics, applying Natural Language Processing (NLP) methods such as concept extraction, word association and sentiment analysis. By drawing on data from a crowdsourced urban planning process in the City of Palo Alto in California, we examine the influence of civic input on the city's Comprehensive City Plan update. The findings show that the impact of citizens' voices depends on the volume and the tone of their demands. A higher demand with a stronger tone results in more policy changes. We also found an interesting and unexpected result: thecity government in Palo Alto mirrors more or less the online crowd's voice while citizen representatives rather filter thanmirror the crowd's will. While NLP methods show promise in making the analysis of the crowdsourced input more efficient, there are several issues. The accuracy rates should be improved. Furthermore, there is still considerable amount of human work in training the algorithm.
This article examines the demographic characteristics, motivations, and expectations of participants in a crowdsourced off-road traffic law reform in Finland. We found that the participants were mainly educated, full-time working professional males with a strong interest in off-road traffic. Though a minority, the women participating in the process produced more ideas than the men. The crowd was motivated by a mix of intrinsic and extrinsic factors. Intrinsic motivations included fulfilling civic duty, affecting the law for sociotropic reasons, to deliberate with and learn from peers. Extrinsic motivations included changing the law for financial gain or other benefits. Participation in crowdsourced policy-making was an act of grassroots advocacy, whether to pursue one's own interest or more altruistic goals, such as protecting nature. The motivations driving the participation were in part similar to those observed in traditional democratic processes, such as elections as well as other online collaborations such as crowdsourced journalism and citizen science. The crowds' behavior was, however, paradoxical. They participated despite the fact that they did not expect that their contributions would affect the law.
This article examines the emergence of democratic deliberation in a crowdsourced law reform process.The empirical context of the study is a crowdsourced legislative reform in Finland, initiated by theFinnish government. The findings suggest that online exchanges in the crowdsourced process qualifyas democratic deliberation according to the classical definition. We introduce the term "crowdsourceddeliberation" to mean an open, asynchronous, depersonalized, and distributed kind of onlinedeliberation occurring among self-selected participants in the context of an attempt by government oranother organization to open up the policymaking or lawmaking process. The article helps tocharacterize the nature of crowdsourced policymaking and to understand its possibilities as a practicefor implementing open government principles. We aim to make a contribution to the literature oncrowdsourcing in policymaking, participatory and deliberative democracy and, specifically, the newlyemerging subfield in deliberative democracy that focuses on "deliberative systems."
This article examines participants' motivation factors to contribute to crowdsourced journalism. Drawing on interviews from cases in which professional journalists used crowdsourcing as a knowledge-search method, the article shows the primary motivation factors are intrinsic, altruistic, and ideological. By sharing information, the crowd wants to contribute to social change and mitigate power and knowledge asymmetries, thus empowering their peers and creating a more informed citizenry. Peer learning and deliberation also drive participation. Participants don't expect tangible rewards like money; instead, they want to contribute to a better society, and crowdsourced journalism becomes a medium for social change and grassroots advocacy. These motivation factors resemble some of those driving Wikipedia creation. The idea of a more equitable society, created by collective knowledge sharing, also drives theparticipation in crowdsourced journalism.
This article examines crowdsourcing as a knowledge-search method and an open journalisticpractice in digital journalism. The study draws on data from four cases in which professionaljournalists used crowdsourcing in their investigations. Crowdsourcing resulted in an efficientknowledge discovery and a continuous flow of tips to journalists and thus benefited journalisticinvestigations. The horizontal and vertical transparency in crowdsourced journalism supportedthe knowledge-search process. However, the high volume of submissions in some casesmade the journalists compromise the journalistic norm of data verification, which resulted inpublishing unverified information. Crowdsourcing as an open journalistic practice thus rupturesjournalistic norms and creates pressure for new ones to emerge, such as blended responsibility,in which the responsibility for data accuracy is shared by the journalists and the readers. Thearticle extends the examination of open journalistic practices and contributes to the understandingof their impact on digital journalism.
This article reports a pioneering case study of a crowdsourced law-reform process in Finland. In the crowdsourcing experiment, the public was invited to contribute to the law-reform process by sharing their knowledge and ideas for a better policy. This article introduces a normative design framework of five principles for crowdsourced policymaking: inclusiveness, accountability, transparency, modularity, and synthesis. Inclusiveness, accountability, and transparency are overarching principles for crowdsourced policymaking. Modularity and synthesis support these overarching principles and are instrumental in achieving the main goals of crowdsourced policymaking, namely, an efficient search for knowledge and democratic deliberation among the participants. These principles apply to both the design of the process and the medium that the process takes place in, i.e., the technology facilitating crowdsourcing. This article analyzes the design of the crowdsourced off-road traffic law experiment in Finland using the five principles described above and provides a future research agenda for examining design aspects in crowdsourced policymaking.
We present theoretical and empirical results demonstrating the usefulness of social choice functions incrowdsourcing for participatory democracies. First, we demonstrate the scalability of social choice functions by defining a natural notion of -approximation, and giving algorithms which efficiently elicit such approximations for two prominent social choice functions: the Borda rule and the Condorcet winner. This result circumvents previous prohibitive lower bounds and is surprisingly strong: even if the number of ideas is as large as the number of participants, each participant will only have to make a logarithmic number of comparisons, an exponential improvement over the linear number of comparisons previously needed. Second, we apply these ideas to Finland's recent off-road traffic law reform, an experimenton participatory democracy in real life. This allows us to verify the scaling predicted in our theoryand show that the constant involved is also not large. In addition, by collecting data on the time that users take to complete rankings of varying sizes, we observe that eliciting partial rankings can further decrease elicitation time as compared to the common method of eliciting pairwise comparisons.
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