Is Participatory Budgeting Coming to a Local Government Near You?


Article by Elizabeth Daigneau:”.. It’s far from a new idea, and you’ve probably been reading about it for years, but participatory budgeting has slowly been growing since it was first introduced in the U.S. in Chicago in 2009. Many anticipate it is about to see a boom as billions of federal dollars continue to pour into local communities…

But with the influx to local communities of billions in federal dollars through the American Rescue Plan Act (ARPA), the Infrastructure Investment and Jobs Act, and the Inflation Reduction Act, many experts think the time is ripe to adopt the tool.

“The stakes are high in restoring and rebuilding our nation’s crumbling civic, political and economic infrastructures,” wrote Hollie Russon Gilman and Lizbeth Lucero of New America’s Political Reform Program in a recent op-ed. “The long overdue improvements needed in America’s cities and countries call for remodeling how we govern and allocate federal funds across the country.”

ARPA dollars prompted the city of Cleveland to push for a participatory budgeting pilot. 

“Cleveland is a city that has one of the higher poverty rates for a city of their size in the United States. They have over 30 percent of their population living below the poverty line,” Kristania De Leon, co-executive director at the Participatory Budgeting Project, said on The Laura Flanders Show’s podcast last July. “So when they found out that they were getting American Rescue Plan Act funds allocated to their municipal government, they said, ‘Wait a minute, this is a huge influx of relatively flexible spending, where’s it going to go and who gets to have a say?’”

A community-led push culminated in a proposal by Cleveland Mayor Justin M. Bibb to the city council last year that $5 million in ARPA funds be allocated to pilot the first citywide participatory budgeting process in its history.

ARPA dollars also elicited Nashville’s city council to allocate $10 million this year to its participatory budgeting program, which is in its third year.

In general, there have been several high-profile participatory budgeting projects in the last year. 

Seattle’s project claims to be the biggest participatory budgeting process ever in the United States. The city council earmarked approximately $30 million in the 2021 budget to run a participatory budgeting process. The goal is to spend the money on initiatives that reduce police violence, reduce crime, and “creating true community safety through community-led safety programs and new investments.”

And in September, New York City Mayor Eric Adams announced the launch of the first-ever citywide participatory budgeting process. The program builds on a 2021 project that engaged residents of the 33 neighborhoods hardest hit by Covid-19 in a $1.3 million participatory budgeting process. The new program invites all New Yorkers, ages 11 and up, to decide how to spend $5 million of mayoral expense funding to address local community needs citywide…(More)”.

Leveraging alternative data to provide loans to the unbanked


Article by Keely Khoury: “Financial inclusion is integral to the achievement of seven of the 17 global SDGs, and the World Bank says in its 2021 report that between 2011 and 2021, “Great strides have been made toward financial inclusion.” However, despite a significant increase in the number of people accessing bank accounts, around 24 per cent of the global population remain unbanked.  

Particularly for minority groups such as immigrants, the ability to access formal financial services is made exponentially more difficult by their lack of permanent address, loss of employment, and gaps in tax records. For small business owners – many of whom provide an essential community service – a lack of formal accounting records, along with any previous time spent unbanked as individuals, contributes to a dearth of information traditionally used to evaluate risk for loans.  

To tackle this issue, US startup Uplinq provides lenders with a ‘credit-assessment-as-a-service’ solution that takes into account the entire business ecosystem, and therefore billions of data points that would not traditionally be examined by underwriters considering a traditional loan application. From supplier references and store traffic to community involvement and property improvements, Uplinq provides a holistic and accurate assessment of the “opportunities, challenges, and interests of each prospect” within “known confidence ranges.” By working with independently audited and fully regulatory-compliant data sets, Uplinq’s services are available worldwide.  

Other innovations that Springwise has spotted that are helping unbanked communities include a Spanish language-first bank, and a free digital learning platform to help underserved communities understand how to better manage their finances…(More)”.

How Democracy Can Win


Essay by Samantha Power: “…At the core of democratic theory and practice is respect for the dignity of the individual. But among the biggest errors many democracies have made since the Cold War is to view individual dignity primarily through the prism of political freedom without being sufficiently attentive to the indignity of corruption, inequality, and a lack of economic opportunity.

This was not a universal blind spot: a number of political figures, advocates, and individuals working at the grassroots level to advance democratic progress presciently argued that economic inequality could fuel the rise of populist leaders and autocratic governments that pledged to improve living standards even as they eroded freedoms. But too often, the activists, lawyers, and other members of civil society who worked to strengthen democratic institutions and protect civil liberties looked to labor movements, economists, and policymakers to address economic dislocation, wealth inequality, and declining wages rather than building coalitions to tackle these intersecting problems.

Democracy suffered as a result. Over the past two decades,as economic inequality rose, polls showed that people in rich and poor countries alike began to lose faith in democracy and worry that young people would end up worse off than they were, giving populists and ethno­nationalists an opening to exploit grievances and gain a political foothold on every continent.

Moving forward, we must look at all economic programming that respects democratic norms as a form of democracy assistance. When we help democratic leaders provide vaccines to their people, bring down inflation or high food prices, send children to school, or reopen markets after a natural disaster, we are demonstrating—in a way that a free press or vibrant civil society cannot always do—that democracy delivers. And we are making it less likely that autocratic forces will take advantage of people’s economic hardship.

Nowhere is that task more important today than in societies that have managed to elect democratic reformers or throw off autocratic or antidemocratic rule through peaceful mass protests or successful political movements. These democratic bright spots are incredibly fragile. Unless reformers solidify their democratic and economic gains quickly, populations understandably grow impatient, especially if they feel that the risks they took to upend the old order have not yielded tangible dividends in their own lives. Such discontent allows opponents of democratic rule—often aided by external autocratic regimes—to wrest back control, reversing reforms and snuffing out dreams of rights-regarding self-government…(More)”.

Digital (In)justice in the Smart City


Book edited by Debra Mackinnon, Ryan Burns and Victoria Fast: “In the contemporary moment, smart cities have become the dominant paradigm for urban planning and administration, which involves weaving the urban fabric with digital technologies. Recently, however, the promises of smart cities have been gradually supplanted by recognition of their inherent inequalities, and scholars are increasingly working to envision alternative smart cities.

Informed by these pressing challenges, Digital (In)Justice in the Smart City foregrounds discussions of how we should think of and work towards urban digital justice in the smart city. It provides a deep exploration of the sources of injustice that percolate throughout a range of sociotechnical assemblages, and it questions whether working towards more just, sustainable, liveable, and egalitarian cities requires that we look beyond the limitations of “smartness” altogether. The book grapples with how geographies impact smart city visions and roll-outs, on the one hand, and how (unjust) geographies are produced in smart pursuits, on the other. Ultimately, Digital (In)Justice in the Smart City envisions alternative cities – smart or merely digital – and outlines the sorts of roles that the commons, utopia, and the law might take on in our conceptions and realizations of better cities…(More)”.

The Sensitive Politics Of Information For Digital States


Essay by Federica Carugati, Cyanne E. Loyle and Jessica Steinberg: “In 2020, Vice revealed that the U.S. military had signed a contract with Babel Street, a Virginia-based company that created a product called Locate X, which collects location data from users across a variety of digital applications. Some of these apps are seemingly innocuous: one for following storms, a Muslim dating app and a level for DIY home repair. Less innocuously, these reports indicate that the U.S. government is outsourcing some of its counterterrorism and counterinsurgency information-gathering activities to a private company.

While states have always collected information about citizens and their activities, advances in digital technologies — including new kinds of data and infrastructure — have fundamentally altered their ability to access, gather and analyze information. Bargaining with and relying on non-state actors like private companies creates tradeoffs between a state’s effectiveness and legitimacy. Those tradeoffs might be unacceptable to citizens, undermining our very understanding of what states do and how we should interact with them …(More)”

LocalView, a database of public meetings for the study of local politics and policy-making in the United State


Paper by Soubhik Barari and Tyler Simko: “Despite the fundamental importance of American local governments for service provision in areas like education and public health, local policy-making remains difficult and expensive to study at scale due to a lack of centralized data. This article introduces LocalView, the largest existing dataset of real-time local government public meetings–the central policy-making process in local government. In sum, the dataset currently covers 139,616 videos and their corresponding textual and audio transcripts of local government meetings publicly uploaded to YouTube–the world’s largest public video-sharing website– from 1,012 places and 2,861 distinct governments across the United States between 2006–2022. The data are processed, downloaded, cleaned, and publicly disseminated (at localview.net) for analysis across places and over time. We validate this dataset using a variety of methods and demonstrate how it can be used to map local governments’ attention to policy areas of interest. Finally, we discuss how LocalView may be used by journalists, academics, and other users for understanding how local communities deliberate crucial policy questions on topics including climate change, public health, and immigration…(More)”.

When Ideology Drives Social Science


Article by Michael Jindra and Arthur Sakamoto: Last summer in these pages, Mordechai Levy-Eichel and Daniel Scheinerman uncovered a major flaw in Richard Jean So’s Redlining Culture: A Data History of Racial Inequality and Postwar Fiction, one that rendered the book’s conclusion null and void. Unfortunately, what they found was not an isolated incident. In complex areas like the study of racial inequality, a fundamentalism has taken hold that discourages sound methodology and the use of reliable evidence about the roots of social problems.

We are not talking about mere differences in interpretation of results, which are common. We are talking about mistakes so clear that they should cause research to be seriously questioned or even disregarded. A great deal of research — we will focus on examinations of Asian American class mobility — rigs its statistical methods in order to arrive at ideologically preferred conclusions.

Most sophisticated quantitative work in sociology involves multivariate research, often in a search for causes of social problems. This work might ask how a particular independent variable (e.g., education level) “causes” an outcome or dependent variable (e.g., income). Or it could study the reverse: How does parental income influence children’s education?

Human behavior is too complicated to be explained by only one variable, so social scientists typically try to “control” for various causes simultaneously. If you are trying to test for a particular cause, you want to isolate that cause and hold all other possible causes constant. One can control for a given variable using what is called multiple regression, a statistical tool that parcels out the separate net effects of several variables simultaneously.

If you want to determine whether income causes better education outcomes, you’d want to compare everyone from a two-parent family, since family status might be another causal factor, for instance. You’d also want to see the effect of family status by comparing everyone with similar incomes. And so on for other variables.

The problem is that there are potentially so many variables that a researcher inevitably leaves some out…(More)”.

Toward a 21st Century National Data Infrastructure: Mobilizing Information for the Common Good


Report by National Academies of Sciences, Engineering, and Medicine: “Historically, the U.S. national data infrastructure has relied on the operations of the federal statistical system and the data assets that it holds. Throughout the 20th century, federal statistical agencies aggregated survey responses of households and businesses to produce information about the nation and diverse subpopulations. The statistics created from such surveys provide most of what people know about the well-being of society, including health, education, employment, safety, housing, and food security. The surveys also contribute to an infrastructure for empirical social- and economic-sciences research. Research using survey-response data, with strict privacy protections, led to important discoveries about the causes and consequences of important societal challenges and also informed policymakers. Like other infrastructure, people can easily take these essential statistics for granted. Only when they are threatened do people recognize the need to protect them…(More)”.

Americans Can’t Consent to Companies Use of their Data


A Report from the Annenberg School for Communication: “Consent has always been a central part of Americans’ interactions with the commercial internet. Federal and state laws, as well as decisions from the Federal Trade Commission (FTC), require either implicit (“opt out”) or explicit (“opt in”) permission from individuals for companies to take and use data about them. Genuine opt out and opt in consent requires that people have knowledge about commercial data-extraction practices as well as a belief they can do something about them. As we approach the 30th anniversary of the commercial internet, the latest Annenberg national survey finds that Americans have neither. High percentages of Americans don’t know, admit they don’t know, and believe they can’t do anything about basic practices and policies around companies’ use of people’s data…
High levels of frustration, concern, and fear compound Americans’ confusion: 80% say they have little control over how marketers can learn about them online; 80% agree that what companies know about them from their online behaviors can harm them. These and related discoveries from our survey paint a picture of an unschooled and admittedly incapable society that rejects the internet industry’s insistence that people will accept tradeoffs for benefits and despairs of its inability to predictably control its digital life in the face of powerful corporate forces. At a time when individual consent lies at the core of key legal frameworks governing the collection and use of personal information, our findings describe an environment where genuine consent may not be possible….The aim of this report is to chart the particulars of Americans’ lack of knowledge about the commercial use of their data and their “dark resignation” in connection to it. Our goal is also to raise questions and suggest solutions about public policies that allow companies to gather, analyze, trade, and otherwise benefit from information they extract from large populations of people who are uninformed about how that information will be used and deeply concerned about the consequences of its use. In short, we find that informed consent at scale is a myth, and we urge policymakers to act with that in mind.”…(More)”.

AI-Ready Open Data


Explainer by Sean Long and Tom Romanoff: “Artificial intelligence and machine learning (AI/ML) have the potential to create applications that tackle societal challenges from human health to climate change. These applications, however, require data to power AI model development and implementation. Government’s vast amount of open data can fill this gap: McKinsey estimates that open data can help unlock $3 trillion to $5 trillion in economic value annually across seven sectors. But for open data to fuel innovations in academia and the private sector, the data must be both easy to find and use. While Data.gov makes it simpler to find the federal government’s open data, researchers still spend up to 80% of their time preparing data into a usable, AI-ready format. As Intel warns, “You’re not AI-ready until your data is.”

In this explainer, the Bipartisan Policy Center provides an overview of existing efforts across the federal government to improve the AI readiness of its open data. We answer the following questions:

  • What is AI-ready data?
  • Why is AI-ready data important to the federal government’s AI agenda?
  • Where is AI-ready data being applied across federal agencies?
  • How could AI-ready data become the federal standard?…(More)”.