Designing Digital Participatory Budgeting Platforms: Urban Biking Activism in Madrid


Paper by Maria Menendez-Blanco & Pernille Bjørn: “Civic technologies have the potential to support participation and influence decision-making in governmental processes. Digital participatory budgeting platforms are examples of civic technologies designed to support citizens in making proposals and allocating budgets. Investigating the empirical case of urban biking activists in Madrid, we explore how the design of the digital platform Decide Madrid impacted the collaborative practices involved in digital participatory budgeting. We found that the design of the platform made the interaction competitive, where individuals sought to gain votes for their single proposals, rather than consider the relations across proposals and the larger context of the city decisions, even if the institutional process rewarded collective support. In this way, the platforms’ design led to forms of individualistic, competitive, and static participation, therefore limiting the possibilities for empowering citizens in scoping and self-regulating participatory budgeting collaboratively. We argue that for digital participatory budgeting platforms to support cooperative engagements they must be revisable and reviewable while supporting accountability among participants and visibility of proposals and activities…(More)”.

Democratic innovation and digital participation


Nesta Report: “Overcoming barriers in democratic innovations to harness the collective intelligence of citizens for a 21st-century democracy.

This report sets out the need for democratic innovations and digital participation tools to move beyond one-off pilots toward more embedded and inclusive systems of decision-making.

This is the first comprehensive analysis of the barriers experienced by democratic innovators around the world. Alongside the barriers, we have captured the enablers that can help advance these innovations and tools to their full potential.

The report is published alongside the advancing democratic innovation toolkit which supports institutions, practitioners and technologists to diagnose the barriers that they face and identify the enablers they can use to address them.

This report is based on insights from global examples of digital democratic innovation, and in particular, three pilots from the COLDIGIT project: a citizens’ assembly in Trondheim, Norway; participatory budgeting in Gothenburg, Sweden; and participatory budgeting in Helsinki, Finland.

The work is a collaboration between Nesta, Digidem Lab, University of Gothenburg, University of Helsinki and SINTEF funded by the Economic and Social Research Council (ESRC)….(More)”.

Exhaustive or Exhausting? Evidence on Respondent Fatigue in Long Surveys


Paper by Dahyeon Jeong et al: “Living standards measurement surveys require sustained attention for several hours. We quantify survey fatigue by randomizing the order of questions in 2-3 hour-long in-person surveys. An additional hour of survey time increases the probability that a respondent skips a question by 10-64%. Because skips are more common, the total monetary value of aggregated categories such as assets or expenditures declines as the survey goes on, and this effect is sizeable for some categories: for example, an extra hour of survey time lowers food expenditures by 25%. We find similar effect sizes within phone surveys in which respondents were already familiar with questions, suggesting that cognitive burden may be a key driver of survey fatigue…(More)”.

Community science draws on the power of the crowd


Essay by Amber Dance: “In community science, also called participatory science, non-professionals contribute their time, energy or expertise to research. (The term ‘citizen science’ is also used but can be perceived as excluding non-citizens.)

Whatever name is used, the approach is more popular than ever and even has journals dedicated to it. The number of annual publications mentioning ‘citizen science’ went from 151 in 2015 to more than 640 in 2021, according to the Web of Science database. Researchers from physiologists to palaeontologists to astronomers are finding that harnessing the efforts of ordinary people is often the best route to the answers they seek.

“More and more funding organizations are actually promoting this type of participatory- and citizen-science data gathering,” says Bálint Balázs, managing director of the Environmental Social Science Research Group in Budapest, a non-profit company focusing on socio-economic research for sustainability.

Community science is also a great tool for outreach, and scientists often delight in interactions with amateur researchers. But it’s important to remember that community science is, foremost, a research methodology like any other, with its own requirements in terms of skill and effort.

“To do a good project, it does require an investment in time,” says Darlene Cavalier, founder of SciStarter, an online clearing house that links research-project leaders with volunteers. “It’s not something where you’re just going to throw up a Google form and hope for the best.” Although there are occasions when scientific data are freely and easily available, other projects create significant costs.

No matter what the topic or approach, people skills are crucial: researchers must identify and cultivate a volunteer community and provide regular feedback or rewards. With the right protocols and checks and balances, the quality of volunteer-gathered data often rivals or surpasses that achieved by professionals.

“There is a two-way learning that happens,” says Tina Phillips, assistant director of the Center for Engagement in Science and Nature at Cornell University in Ithaca, New York. “We all know that science is better when there are more voices, more perspectives.”…(More)”

The End of Real Social Networks


Essay by Daron Acemoglu: “Social media platforms are not only creating echo chambers, propagating falsehoods, and facilitating the circulation of extremist ideas. Previous media innovations, dating back at least to the printing press, did that, too, but none of them shook the very foundations of human communication and social interaction.

CAMBRIDGE – Not only are billions of people around the world glued to their mobile phones, but the information they consume has changed dramatically – and not for the better. On dominant social-media platforms like Facebook, researchers have documented that falsehoods spread faster and more widely than similar content that includes accurate information. Though users are not demanding misinformation, the algorithms that determine what people see tend to favor sensational, inaccurate, and misleading content, because that is what generates “engagement” and thus advertising revenue.

As the internet activist Eli Pariser noted in 2011, Facebook also creates filter bubbles, whereby individuals are more likely to be presented with content that reinforces their own ideological leanings and confirms their own biases. And more recent research has demonstrated that this process has a major influence on the type of information users see.

Even leaving aside Facebook’s algorithmic choices, the broader social-media ecosystem allows people to find subcommunities that align with their interests. This is not necessarily a bad thing. If you are the only person in your community with an interest in ornithology, you no longer have to be alone, because you can now connect with ornithology enthusiasts from around the world. But, of course, the same applies to the lone extremist who can now use the same platforms to access or propagate hate speech and conspiracy theories.

No one disputes that social-media platforms have been a major conduit for hate speech, disinformation, and propaganda. Reddit and YouTube are breeding grounds for right-wing extremism. The Oath Keepers used Facebook, especially, to organize their role in the January 6, 2021, attack on the United States Capitol. Former US President Donald Trump’s anti-Muslim tweets were found to have fueled violence against minorities in the US.

True, some find such observations alarmist, noting that large players like Facebook and YouTube (which is owned by Google/Alphabet) do much more to police hate speech and misinformation than their smaller rivals do, especially now that better moderation practices have been developed. Moreover, other researchers have challenged the finding that falsehoods spread faster on Facebook and Twitter, at least when compared to other media.

Still others argue that even if the current social-media environment is treacherous, the problem is transitory. After all, novel communication tools have always been misused. Martin Luther used the printing press to promote not just Protestantism but also virulent anti-Semitism. Radio proved to be a powerful tool in the hands of demagogues like Father Charles Coughlin in the US and the Nazis in Germany. Both print and broadcast outlets remain full of misinformation to this day, but society has adjusted to these media and managed to contain their negative effects…(More)”.

Collection of Case Studies of Institutional Adoption of Citizen Science


About TIME4CS : “The first objective was to increase our knowledge about the actions leading to institutional changes in RPOs (which are necessary to promote CS in science and technology) through a complete and up-to-date picture based upon the identification, mapping, monitoring and analysis of ongoing CS practices. To accomplish this objective, we, the TIME4CS project team, have collected and analysed 37 case studies on the institutional adoption of Citizen Science and Open Science around the world, which this article addresses.

For an organisation to open up and accept data and information that was produced outside it, with a different framework for data collection and quality assurance, there are multiple challenges. These include existing practices and procedures, legal obligations, as well as resistance from within due to framing of such action as a threat. Research that was carried out with multiple international case studies (Haklay et al. 2014; GFDRR 2018), demonstrated the importance of different institutional and funding structures needed to enable such activities and the use of the resulting information…(More)”.

Participatory Data Governance: How Small Changes Can Lead to Greater Inclusion


Essay by Kate Richards and Martina Barbero: “What the majority of participatory data governance approaches have in common is strong collaboration between public authorities and civil society organizations and representatives of communities that have been historically marginalized and excluded or who are at risk of being marginalized. This leads to better data and evidence for policy-making. For instance, a partnership between the Canadian government and First Nations communities led Statistics Canada to better understand the factors that exacerbate exclusion and capture the lived experiences of these communities. 

These practices are pivotal for increasing inclusion and accountability in data beyond the data collection stage. In fact, while inclusion at the data collection phase remains extremely important, participatory data governance approaches can be adopted at any stage of the data lifecycle.

  • Before data collection starts: Building relationships with communities at risk of being marginalized helps clarify “what to count” and how to embed the needs and aspirations of vulnerable populations in new data collection approaches. The National Department of Statistics in Colombia’s (DANE) multi-year work with Indigenous communities enabled the statistical office to change their population survey approach, leading to more inclusive data policies. 
  • After data is collectedCollaborating with civil society organizations enables public authorities to assess how and through which channels data should be shared with target communities. When the government of Buenos Aires wanted to provide information to increase access to sexual and reproductive health services, it worked with civil society to gather feedback and develop a platform that would be useful and accessible to the target population.
  • At the stage of data use: Participatory approaches for data inclusion also support greater data use, both by public authorities and by external stakeholders. In Medellin, Colombia, the availability of more granular and more inclusive data on teen pregnancy enabled the government to develop better prevention policies and establish personalized services for girls at risk, resulting in a reduction of teen pregnancies by 30%. In Rosario, Argentina, the government’s partnership with associations representing persons with disabilities led to the development of much more accessible and inclusive public portals, which in turn resulted in better access to services for all citizens…(More)”.

Crowdsourced Politics


Book by Ariadne Vromen, Darren Halpin, Michael Vaughan: “This book focuses on online petitioning and crowdfunding platforms to demonstrate the everyday impact that digital communications have had on contemporary citizen participation. It argues that crowdsourced participation has become normalised and institutionalised into the repertoires of citizens and their organisations. 

To illustrate their arguments the authors use an original survey on acts of political engagement, undertaken with Australian citizens. Through detailed interviews and online analysis they show how advocacy organisations now use online petitions for strategic interventions and mobilisation. They also analyse the policy issues that mobilise citizens on crowdsourcing platforms, including a unique dataset of 17,000 petitions from the popular non-government platform, Change.org. Contrasting mass public concerns with the policy agenda of the government of the day shows there is a disjuncture and lack of responsiveness to crowdsourced citizen expression. Ultimately the book explores the long-term implications of citizen-led change for democracy. ..(More)”.

Collective Intelligence


Editorial to the Inaugural Issue by Jessica Flack et al: “It is easy to see the potential of collective intelligence research to serve as a unifying force in the sciences. Its “nuts and bolts” methodological and conceptual questions apply across scales – how to characterize minimal and optimal algorithms for aggregating and storing information; how to derive macroscopic collective outputs from microscopic inputs; how to measure the robustness and vulnerability of collective outcomes, the design of algorithms for information aggregation; the role of diversity in forecasting and estimation; the dynamics of problem-solving in groups; team dynamics and complementary and synergistic roles; open innovation processes, and, more recently, the practical options for combining artificial and collective intelligence.

Despite this potential, the collective intelligence scholarly community is currently distributed over somewhat independent clusters of fields and research groups. We hope to bring these groups together. In this spirit, we will provide space for cross-cutting research aimed at principles of collective intelligence but also for field-specific research.

How should we understand the objectives of collective intelligence in different contexts? These can include identifying an object, making predictions, solving a problem, taking action, achieving an outcome, surviving in a dynamic environment, or a combination of these. Clarity on objectives is essential to measure or evaluate collective intelligence.

What can we learn about how collective intelligence addresses different types of problems, such as the characteristics of static, stochastic, and dynamic environments? For example, if stochastic, is the distribution of states best described as coming from a fixed distribution, as produced by a Markov Process, or as deeply uncertain? If a multi-agent system, to what extent do those entities cooperate or compete? What combinations of hierarchies and various forms of self-organization–such as markets, democracies, and communities–can align goals and coordinate actions?

What causes collective intelligence? How are the core processes needed for intelligence–such as sensing, deciding, and learning–performed in very different types of collective systems? What precisely is the relationship between diversity and collective intelligence (where the patterns are much more complex than often assumed)? Or the roles of synchrony and synergy in teams? What are some non-obvious patterns, such as how a slow learning rate among some population members maintains memory? What is the role of noise (as discussed in our first published dialogue), which, while harmful to the individual, can be potentially beneficial for the collective? When can a propensity for mistakes be helpful?

How should we understand the relationships between levels? For example, can aggregate or macroscale variables be derived from microscale interactions and mechanisms, or vice-versa?

Where does collective intelligence reside, and how is it “stored”—in individual heads, encoded in interaction networks and circuits, or embodied in the interaction of a group with its environment?

How are trade-offs handled in different contexts–speed and accuracy, focus and peripheral vision, exploration and exploitation?

These–and dozens of related questions–are relevant to many disciplines, and each may benefit from insights derived from others, particularly if we can develop common principles and concepts…(More)”.

Citizen science in environmental and ecological sciences


Paper by Dilek Fraisl et al: “Citizen science is an increasingly acknowledged approach applied in many scientific domains, and particularly within the environmental and ecological sciences, in which non-professional participants contribute to data collection to advance scientific research. We present contributory citizen science as a valuable method to scientists and practitioners within the environmental and ecological sciences, focusing on the full life cycle of citizen science practice, from design to implementation, evaluation and data management. We highlight key issues in citizen science and how to address them, such as participant engagement and retention, data quality assurance and bias correction, as well as ethical considerations regarding data sharing. We also provide a range of examples to illustrate the diversity of applications, from biodiversity research and land cover assessment to forest health monitoring and marine pollution. The aspects of reproducibility and data sharing are considered, placing citizen science within an encompassing open science perspective. Finally, we discuss its limitations and challenges and present an outlook for the application of citizen science in multiple science domains…(More)”.