Principles and Practices for a Federal Statistical Agency


National Academies of Sciences Report: “Publicly available statistics from government agencies that are credible, relevant, accurate, and timely are essential for policy makers, individuals, households, businesses, academic institutions, and other organizations to make informed decisions. Even more, the effective operation of a democratic system of government depends on the unhindered flow of statistical information to its citizens.

In the United States, federal statistical agencies in cabinet departments and independent agencies are the governmental units whose principal function is to compile, analyze, and disseminate information for such statistical purposes as describing population characteristics and trends, planning and monitoring programs, and conducting research and evaluation. The work of these agencies is coordinated by the U.S. Office of Management and Budget. Statistical agencies may acquire information not only from surveys or censuses of people and organizations, but also from such sources as government administrative records, private-sector datasets, and Internet sources that are judged of suitable quality and relevance for statistical use. They may conduct analyses, but they do not advocate policies or take partisan positions. Statistical purposes for which they provide information relate to descriptions of groups and exclude any interest in or identification of an individual person, institution, or economic unit.

Four principles are fundamental for a federal statistical agency: relevance to policy issues, credibility among data users, trust among data providers, and independence from political and other undue external influence.� Principles and Practices for a Federal Statistical Agency: Sixth Edition presents and comments on these principles as they’ve been impacted by changes in laws, regulations, and other aspects of the environment of federal statistical agencies over the past 4 years….(More)”.

Lessons from Airbnb and Uber to Open Government as a Platform


Interview by Marquis Cabrera with Sangeet Paul Choudary: “…Platform companies have a very strong core built around data, machine learning, and a central infrastructure. But they rapidly innovate around it to try and test new things in the market and that helps them open themselves for further innovation in the ecosystem. Governments can learn to become more modular and more agile, the way platform companies are. Modularity in architecture is a very fundamental part of being a platform company; both in terms of your organizational architecture, as well as your business model architecture.

The second thing that governments can learn from a platform company is that successful platform companies are created with intent. They are not created by just opening out what you have available. If you look at the current approach of applying platform thinking in government, a common approach is just to take data and open it out to the world. However, successful platform companies first create a shaping strategy to shape-out and craft a direction of vision for the ecosystem in terms of what they can achieve by being on the platform. They then provision the right tools and services that serve the vision to enable success for the ecosystem[1] . And only then do they open up their infrastructure. It’s really important that you craft the right shaping strategy and use that to define the rights tools and services before you start pursuing a platform implementation.

In my work with governments, I regularly find myself stressing the importance of thinking as a market maker rather than as a service provider. Governments have always been market makers but when it comes to technology, they often take the service provider approach.

In your book, you used San Francisco City Government and Data.gov as examples of infusing platform thinking in government. But what are some global examples of governments, countries infusing platform thinking around the world?

One of the best examples is from my home country Singapore, which has been at the forefront of converting the nation into a platform. It has now been pursuing platform strategy both overall as a nation by building a smart nation platform, and also within verticals. If you look particularly at mobility and transportation, it has worked to create a central core platform and then build greater autonomy around how mobility and transportation works in the country. Other good examples of governments applying this are Dubai, South Korea, Barcelona; they are all countries and cities that have applied the concept of platforms very well to create a smart nation platform. India is another example that is applying platform thinking with the creation of the India stack, though the implementation could benefit from better platform governance structures and a more open regulation around participation….(More)”.

The role of Open Data in driving sustainable mobility in nine smart cities


Paper by Piyush Yadav et al: “In today’s era of globalization, sustainable mobility is considered as a key factor in the economic growth of any country. With the emergence of open data initiatives, there is tremendous potential to improve mobility. This paper presents findings of a detailed analysis of mobility open data initiatives in nine smart cities – Amsterdam, Barcelona, Chicago, Dublin, Helsinki, London, Manchester, New York and San Francisco. The paper discusses the study of various sustainable indicators in the mobility domain and its convergence with present open datasets. Specifically, it throws light on open data ecosystems in terms of their production and consumption. It gives a comprehensive view of the nature of mobility open data with respect to their formats, interactivity, and availability. The paper details the open datasets in terms of their alignment with different mobility indicators, publishing platforms, applications and API’s available. The paper discusses how these open datasets have shown signs of fostering organic innovation and sustainable growth in smart cities with impact on mobility trends. The results of the work can be used to inform the design of data driven sustainable mobility in smart cities to maximize the utilization of available open data resources….(More)”.

Using Collaboration to Harness Big Data for Social Good


Jake Porway at SSIR: “These days, it’s hard to get away from the hype around “big data.” We read articles about how Silicon Valley is using data to drive everything from website traffic to autonomous cars. We hear speakers at social sector conferences talk about how nonprofits can maximize their impact by leveraging new sources of digital information like social media data, open data, and satellite imagery.

Braving this world can be challenging, we know. Creating a data-driven organization can require big changes in culture and process. Some nonprofits, like Crisis Text Line and Watsi, started off boldly by building their own data science teams. But for the many other organizations wondering how to best use data to advance their mission, we’ve found that one ingredient works better than all the software and tech that you can throw at a problem: collaboration.

As a nonprofit dedicated to applying data science for social good, DataKind has run more than 200 projects in collaboration with other nonprofits worldwide by connecting them to teams of volunteer data scientists. What do the most successful ones have in common? Strong collaborations on three levels: with data science experts, within the organization itself, and across the nonprofit sector as a whole.

1. Collaborate with data science experts to define your project. As we often say, finding problems can be harder than finding solutions. ….

2. Collaborate across your organization to “build with, not for.” Our projects follow the principles of human-centered design and the philosophy pioneered in the civic tech world of “design with, not for.” ….

3. Collaborate across your sector to move the needle. Many organizations think about building data science solutions for unique challenges they face, such as predicting the best location for their next field office. However, most of us are fighting common causes shared by many other groups….

By focusing on building strong collaborations on these three levels—with data experts, across your organization, and across your sector—you’ll go from merely talking about big data to making big impact….(More).

The Politics of Listening: Possibilities and Challenges for Democratic Life


Book by Leah Bassel: “…explores listening as a social and political practice, in contrast to the more common focus on voice and speaking.  The author draws on cases from Canada, France and the United Kingdom, exploring: minority women and debates over culture and religion; riots and young men in France and England; citizen journalism and the creative use of different media; and solidarity between migrant justice and indigenous activists. Analysis across these diverse settings considers whether and how a politics of listening, which demands that the roles of speakers and listeners change, can be undertaken in adversarial and tense political moments. The Politics of Listening argues that such a practice has the potential to create new ways of being and acting together, as political equals who are heard on their own terms….(More)”

Reinvention in Middle America


New report by sparks & honey: “Conventional wisdom suggests that to peer into the crystal ball of America’s future, one should go to Silicon Valley to check out the latest start-up unicorns, or to New York or Los Angeles to scout emerging trends in fashion and food.
Middle America, on the other hand, is often described as if it’s on the margins of culture and innovation — “flyover country” — provincial, unsophisticated and stuck in the past. But Middle America is diverse and although it is not stuck in the past —rhetoric about it is.

In this culture forecast report, we spotlight the region, looking at it not through the lens of politics, ideology or outdated clichés, but rather through innovation. Key cities from Cleveland to Nashville to Louisville are reinventing themselves by embracing innovation in manufacturing, city design, healthcare, sustainability efforts and clean energy, creatively solving problems that the entire country will eventually have to confront. And they’re imbuing this reinvention with characteristic Middle American values of community, collaboration, and concern for the social impact of their actions.

Yes, portions of Middle America may have a lot of cornfields — but drone-farming is happening there. Although Nashville is still the seat of the Grand Ole Opry, it’s also emerging as a major fashion and design hub. And in Appalachia, a coal museum is powered by solar energy and out-of-work coal miners are reinventing themselves as coders. It’s even predicted that in five years, the Midwest will have more startups than Silicon Valley.

Although it’s easy to politicize and divide America, innovation is not about moving right or left. Innovation is about moving forward…(More)”

A Road-Map To Transform The Secure And Accessible Use Of Data For High Impact Program Management, Policy Development, And Scholarship


Preface and Roadmap by Andrew Reamer and Julia Lane: “Throughout the United States, there is broadly emerging support to significantly enhance the nation’s capacity for evidence-based policymaking. This support is shared across the public and private sectors and all levels of geography. In recent years, efforts to enable evidence-based analysis have been authorized by the U.S. Congress, and funded by state and local governments, philanthropic foundations.

The potential exists for substantial change. There has been dramatic growth in technological capabilities to organize, link, and analyze massive volumes of data from multiple, disparate sources. A major resource is administrative data, which offer both advantages and challenges in comparison to data gathered through the surveys that have been the basis for much policymaking to date. To date, however, capability-building efforts have been largely “artisanal” in nature. As a result, the ecosystem of evidence-based policymaking capacity-building efforts is thin and weakly connected.

Each attempt to add a node to the system faces multiple barriers that require substantial time, effort, and luck to address. Those barriers are systemic. Too much attention is paid to the interests of researchers, rather than in the engagement of data producers. Individual projects serve focused needs and operate at a relative distance from one another Researchers, policymakers and funding agencies thus need exists to move from these artisanal efforts to new, generalized solutions that will catalyze the creation of a robust, large-scale data infrastructure for evidence-based policymaking.

This infrastructure will have be a “complex, adaptive ecosystem” that expands, regenerates, and replicates as needed while allowing customization and local control. To create a path for achieving this goal, the U.S. Partnership on Mobility from Poverty commissioned 12 papers and then hosted a day-long gathering (January 23, 2017) of over 60 experts to discuss findings and implications for action. Funded by the Gates Foundation, the papers and workshop panels were organized around three topics: privacy and confidentiality, data providers, and comprehensive strategies.

This issue of the Annals showcases those 12 papers which jointly propose solutions for catalyzing the development of a data infrastructure for evidence-based policymaking.

This preface:

  • places current evidence-based policymaking efforts in historical context
  • briefly describes the nature of multiple current efforts,
  • provides a conceptual framework for catalyzing the growth of any large institutional ecosystem,
  • identifies the major dimensions of the data infrastructure ecosystem,
  • describes key barriers to the expansion of that ecosystem, and
  • suggests a roadmap for catalyzing that expansion….(More)

(All 12 papers can be accessed here).

The Age of Customer.gov: Can the Tech that Drives 311 Help Government Deliver an Amazon-like Experience?


Tod Newcombe  at GovTech: “The Digital Communities Special … June 2017 report explores the idea that the tech that drives 311 can help government deliver an Amazon-like experience.

PART 1: 311: FROM A HOTLINE TO A PLATFORM FOR CITIZEN ENGAGEMENT

PART 2: CLOUD 311 POPULARITY GROWS AS CITIES OF ALL SIZES MOVE TO REMOTELY HOSTED CRM

PART 3: THE FUTURE OF CRM AND CUSTOMER SERVICE: LOOK TO BOSTON

PART 4: CRM USE IS GAINING TRACTION IN LOCAL GOVERNMENT — HERE ARE THE NUMBERS TO PROVE IT…(More)”.

Computational Propaganda Worldwide


Executive Summary: “The Computational Propaganda Research Project at the Oxford Internet Institute, University of Oxford, has researched the use of social media for public opinion manipulation. The team involved 12 researchers across nine countries who, altogether, interviewed 65 experts, analyzed tens of millions posts on seven different social media platforms during scores of elections, political crises, and national security incidents. Each case study analyzes qualitative, quantitative, and computational evidence collected between 2015 and 2017 from Brazil, Canada, China, Germany, Poland, Taiwan, Russia, Ukraine, and the United States.

Computational propaganda is the use of algorithms, automation, and human curation to purposefully distribute misleading information over social media networks. We find several distinct global trends in computational propaganda. •

  • Social media are significant platforms for political engagement and crucial channels for disseminating news content. Social media platforms are the primary media over which young people develop their political identities.
    • In some countries this is because some companies, such as Facebook, are effectively monopoly platforms for public life. o In several democracies the majority of voters use social media to share political news and information, especially during elections.
    • In countries where only small proportions of the public have regular access to social media, such platforms are still fundamental infrastructure for political conversation among the journalists, civil society leaders, and political elites.
  • Social media are actively used as a tool for public opinion manipulation, though in diverse ways and on different topics. o In authoritarian countries, social media platforms are a primary means of social control. This is especially true during political and security crises. o In democracies, social media are actively used for computational propaganda either through broad efforts at opinion manipulation or targeted experiments on particular segments of the public.
  • In every country we found civil society groups trying, but struggling, to protect themselves and respond to active misinformation campaigns….(More)”.

Inside the Algorithm That Tries to Predict Gun Violence in Chicago


Gun violence in Chicago has surged since late 2015, and much of the news media attention on how the city plans to address this problem has focused on the Strategic Subject List, or S.S.L.

The list is made by an algorithm that tries to predict who is most likely to be involved in a shooting, either as perpetrator or victim. The algorithm is not public, but the city has now placed a version of the list — without names — online through its open data portal, making it possible for the first time to see how Chicago evaluates risk.

We analyzed that information and found that the assigned risk scores — and what characteristics go into them — are sometimes at odds with the Chicago Police Department’s public statements and cut against some common perceptions.

■ Violence in the city is less concentrated at the top — among a group of about 1,400 people with the highest risk scores — than some public comments from the Chicago police have suggested.

■ Gangs are often blamed for the devastating increase in gun violence in Chicago, but gang membership had a small predictive effect and is being dropped from the most recent version of the algorithm.

■ Being a victim of a shooting or an assault is far more predictive of future gun violence than being arrested on charges of domestic violence or weapons possession.

■ The algorithm has been used in Chicago for several years, and its effectiveness is far from clear. Chicago accounted for a large share of the increase in urban murders last year….(More)”.