Political Inequality in Affluent Democracies


 for the SSRC: “A key characteristic of a democracy,” according to Robert Dahl, is “the continuing responsiveness of the government to the preferences of its citizens, considered as political equals.” Much empirical research over the past half century, most of it focusing on the United States, has examined the relationship between citizens’ policy preferences and the policy choices of elected officials. According to Robert Shapiro, this research has generated “evidence for strong effects of public opinion on government policies,” providing “a sanguine picture of democracy at work.”

In recent years, however, scholars of American politics have produced striking evidence that the apparent “strong effects” of aggregate public opinion in these studies mask severe inequalities in responsiveness. As Martin Gilens put it, “The American government does respond to the public’s preferences, but that responsiveness is strongly tilted toward the most affluent citizens. Indeed, under most circumstances, the preferences of the vast majority of Americans appear to have essentially no impact on which policies the government does or doesn’t adopt.”

One possible interpretation of these findings is that the American political system is anomalous in its apparent disregard for the preferences of middle-class and poor people. In that case, the severe political inequality documented there would presumably be accounted for by distinctive features of the United States, such as its system of private campaign finance, its weak labor unions, or its individualistic political culture. But, what if severe political inequality is endemic in affluent democracies? That would suggest that fiddling with the political institutions of the United States to make them more like Denmark’s (or vice versa) would be unlikely to bring us significantly closer to satisfying Dahl’s standard of democratic equality. We would be forced to conclude either that Dahl’s standard is fundamentally misguided or that none of the political systems commonly identified as democratic comes anywhere close to meriting that designation.

Analyzing policy responsiveness

“I have attempted to test the extent to which policymakers in a variety of affluent democracies respond to the preferences of their citizens considered as political equals.”

To address this question, I have attempted to test the extent to which policymakers in a variety of affluent democracies respond to the preferences of their citizens considered as political equals. My analyses focus on the relationship between public opinion and government spending on social welfare programs, including pensions, health, education, and unemployment benefits. These programs represent a major share of government spending in every affluent democracy and, arguably, an important source of public well-being. Moreover, social spending figures prominently in the comparative literature on the political impact of public opinion in affluent democracies, with major scholarly works suggesting that it is significantly influenced by citizens’ preferences.

My analyses employ data on citizens’ views about social spending and the welfare state from three major cross-national survey projects—the International Social Survey Programme (ISSP), the World Values Survey (WVS), and the European Values Survey (EVS). In combination, these three sources provide relevant opinion data from 160 surveys conducted between 1985 and 2012 in 30 countries, including most of the established democracies of Western Europe and the English-speaking world and some newer democracies in Eastern Europe, Latin America, and Asia. I examine shifts in (real per capita) social spending in the two years following each survey. Does greater public enthusiasm for the welfare state lead to increases in social spending, other things being equal? And, more importantly here, do the views of low-income people have the same apparent influence on policy as the views of affluent people?…(More)”.

Intelligent sharing: unleashing the potential of health and care data in the UK to transform outcomes


Report by Future Care Capital: “….Data is often referred to as the ‘new oil’ – the 21st century raw material which, when hitched to algorithmic refinement, may be mined for insight and value – and ‘data flows’ are said to have exerted a greater impact upon global growth than traditional goods flows in recent years (Manyika et al, 2016). Small wonder, then, that governments around the world are endeavouring to strike a balance between individual privacy rights and protections on the one hand, and organisational permissions to facilitate the creation of social, economic and environmental value from broad-ranging data on the other: ‘data rights’ are now of critical importance courtesy of technological advancements. The tension between the two is particularly evident where health and care data in the UK is concerned. Individuals are broadly content with anonymised data from their medical records being used for public benefit but are, understandably, anxious about the implications of the most intimate aspects of their lives being hacked or, else, shared without their knowledge or consent….

The potential for health and care data to be transformative remains, and there is growing concern that opportunities to improve the use of health and care data in peoples’ interests are being missed….

we recommend additional support for digitisation efforts in social care settings. We call upon the Government to streamline processes associated with Information Governance (IG) modelling to help data sharing initiatives that traverse organisational boundaries. We also advocate for investment and additional legal safeguards to make more anonymised data sets available for research and innovation. Crucially, we recommend expediting the scope for individuals to contribute health and care data to sharing initiatives led by the public sector through promotion, education and pilot activities – so that data is deployed to transform public health and support the ‘pivot to prevention’.

In Chapter Two, we explore the rationale and scope for the UK to build upon emergent practice from around the world and become a global leader in ‘data philanthropy’ – to push at the boundaries of existing plans and programmes, and support the development of and access to unrivalled health and care data sets. We look at member-controlled ‘data cooperatives’ and what we’ve termed ‘data communities’ operated by trusted intermediaries. We also explore ‘data collaboratives’ which involve the private sector engaging in data philanthropy for public benefit. Here, we make recommendations about promoting a culture of data philanthropy through the demonstration of tangible benefits to participants and the wider public, and we call upon Government to assess the appetite and feasibility of establishing the world’s first National Health and Care Data Donor Bank….(More)”

 

Open Data Blueprint


ODX Canada: “In Canada, the open data environment should be viewed as a supply chain. The movement of open data from producers to consumers involves many different organizations, people, activities, projects and initiatives, all of which work together to push out a final product. Naturally, if there is a break or hurdle in this supply chain, it doesn’t work efficiently. A fundamental hurdle highlighted by companies across the country was the inability to scale their business at the provincial, national and international levels.

This blueprint aims to address the challenges Canadian entrepreneurs are facing by encouraging municipalities to launch open data initiatives. By sharing best practices, we hope to encourage the accessibility of datasets within existing jurisdictions. The structured recommendations in this Open Data Blueprint are based on feedback and best practices seen in major cities across Canada collected through ODX’s primary research….(More)”

(Read more about the OD150 initiative here)

Innovation for the Sustainable Development Goals


UNDP: “In 2014, UNDP, with the generous support of the Government of Denmark, established an Innovation Facility to improve service delivery and support national governments and citizens to tackle complex challenges.

The report ‘Spark, Scale, Sustain’ shares UNDP’s approach to innovation, over 40 case studies of innovation for the Sustainable Development Goals in practice and Features on Alternative Finance, Behavioral Insights, Data Innovation and Public Policy Labs.

Download the report to find out more about the innovation initiatives that are testing and scaling solutions to address challenges across five areas:

  • Eradicate Poverty, Leave No One Behind
  • Protect the Planet
  • Build Peaceful Societies, Prevent Violent Conflict
  • Manage Risk, Improve Disaster Response
  • Advance Gender Equality & Women’s Empowerment….(More)”.

NIH-funded team uses smartphone data in global study of physical activity


National Institutes of Health: “Using a larger dataset than for any previous human movement study, National Institutes of Health-funded researchers at Stanford University in Palo Alto, California, have tracked physical activity by population for more than 100 countries. Their research follows on a recent estimate that more than 5 million people die each year from causes associated with inactivity.

The large-scale study of daily step data from anonymous smartphone users dials in on how countries, genders, and community types fare in terms of physical activity and what results may mean for intervention efforts around physical activity and obesity. The study was published July 10, 2017, in the advance online edition of Nature.

“Big data is not just about big numbers, but also the patterns that can explain important health trends,” said Grace Peng, Ph.D., director of the National Institute of Biomedical Imaging and Bioengineering (NIBIB) program in Computational Modeling, Simulation and Analysis.

“Data science and modeling can be immensely powerful tools. They can aid in harnessing and analyzing all the personalized data that we get from our phones and wearable devices.”

Almost three quarters of adults in developed countries and half of adults in developing economies carry a smartphone. The devices are equipped with tiny accelerometers, computer chip that maintains the orientation of the screen, and can also automatically record stepping motions. The users whose data contributed to this study subscribed to the Azumio Argus app, a free application for tracking physical activity and other health behaviors….

In addition to the step records, the researchers accessed age, gender, and height and weight status of users who registered the smartphone app. They used the same calculation that economists use for income inequality — called the Gini index — to calculate activity inequality by country.

“These results reveal how much of a population is activity-rich, and how much of a population is activity-poor,” Delp said. “In regions with high activity inequality there are many people who are activity poor, and activity inequality is a strong predictor of health outcomes.”…

The researchers investigated the idea that making improvements in a city’s walkability — creating an environment that is safe and enjoyable to walk — could reduce activity inequality and the activity gender gap.

“If you must cross major highways to get from point A to point B in a city, the walkability is low; people rely on cars,” Delp said. “In cities like New York and San Francisco, where you can get across town on foot safely, the city has high walkability.”

Data from 69 U.S. cities showed that higher walkability scores are associated with lower activity inequality. Higher walkability is associated with significantly more daily steps across all age, gender, and body-mass-index categories.  However, the researchers found that women recorded comparatively less activity than men in places that are less walkable.

The study exemplifies how smartphones can deliver new insights about key health behaviors, including what the authors categorize as the global pandemic of physical inactivity….(More)”.

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)”.

The ethics issue: Should we abandon privacy online?


Special issue of the New Scientist: “Those who would give up essential Liberty to purchase a little temporary Safety,” Benjamin Franklin once said, “deserve neither Liberty nor Safety.” But if Franklin were alive today, where would he draw the line? Is the freedom to send an encrypted text message essential? How about the right to keep our browsing history private? What is the sweet spot between our need to be left alone and our desire to keep potential criminals from communicating in secret?

In an age where fear of terrorism is high in the public consciousness, governments are likely to err on the side of safety. Over the past decade, the authorities have been pushing for – and getting – greater powers of surveillance than they have ever had, all in the name of national security.

The downsides are not immediately obvious. After all, you might think you have nothing to hide. But most of us have perfectly legal secrets we’d rather someone else didn’t see. And although the chances of the authorities turning up to take you away in a black SUV on the basis of your WhatsApp messages are small in free societies, the chances of insurance companies raising your premiums are not….(More)”.

Open data: Accountability and transparency


 at Big Data and Society: “The movements by national governments, funding agencies, universities, and research communities toward “open data” face many difficult challenges. In high-level visions of open data, researchers’ data and metadata practices are expected to be robust and structured. The integration of the internet into scientific institutions amplifies these expectations. When examined critically, however, the data and metadata practices of scholarly researchers often appear incomplete or deficient. The concepts of “accountability” and “transparency” provide insight in understanding these perceived gaps. Researchers’ primary accountabilities are related to meeting the expectations of research competency, not to external standards of data deposition or metadata creation. Likewise, making data open in a transparent way can involve a significant investment of time and resources with no obvious benefits. This paper uses differing notions of accountability and transparency to conceptualize “open data” as the result of ongoing achievements, not one-time acts….(More)”.

Avoiding Garbage In – Garbage Out: Improving Administrative Data Quality for Research


Blog by : “In June, I presented the webinar, “Improving Administrative Data Quality for Research and Analysis”, for members of the Association of Public Data Users (APDU). APDU is a national network that provides a venue to promote education, share news, and advocate on behalf of public data users.

The webinar served as a primer to help smaller organizations begin to use their data for research. Participants were given the tools to transform their administrative data into “research-ready” datasets.

I first reviewed seven major issues for administrative data quality and discussed how these issues can affect research and analysis. For instance, issues with incorrect value formats, unit of analysis, and duplicate records can make the data difficult to use. Invalid or inconsistent values lead to inaccurate analysis results. Missing or outlier values can produce inaccurate and biased analysis results. All these issues make the data less useful for research.

Next, I presented concrete strategies for reviewing the data to identify each of these quality issues. I also discussed several tips to make the data review process easier, faster, and easy to replicate. Most importantly among these tips are: (1) reviewing everyvariable in the data set, whether you expect problems or not, and (2) relying on data documentation to understand how the data should look….(More)”.

Data for Development: The Case for Information, Not Just Data


Daniela Ligiero at the Council on Foreign Relations: “When it comes to development, more data is often better—but in the quest for more data, we can often forget about ensuring we have information, which is even more valuable. Information is data that have been recorded, classified, organized, analyzed, interpreted, and translated within a framework so that meaning emerges. At the end of the day, information is what guides action and change.

The need for more data

In 2015, world leaders came together to adopt a new global agenda to guide efforts over the next fifteen years, the Sustainable Development Goals. The High-level Political Forum (HLPF), to be held this year at the United Nations on July 10-19, is an opportunity for review of the 2030 Agenda, and will include an in-depth analysis of seven of the seventeen goals—including those focused on poverty, health, and gender equality. As part of the HLPF, member states are encouraged to undergo voluntary national reviews of progress across goals to facilitate the sharing of experiences, including successes, challenges, and lessons learned; to strengthen policies and institutions; and to mobilize multi-stakeholder support and partnerships for the implementation of the agenda.

A significant challenge that countries continue to face in this process, and one that becomes painfully evident during the HLPF, is the lack of data to establish baselines and track progress. Fortunately, new initiatives aligned with the 2030 Agenda are working to focus on data, such as the Global Partnership for Sustainable Development Data. There are also initiatives focus on collecting more and better data in particular areas, like gender data (e.g., Data2X; UN Women’s Making Every Girl and Woman Count). This work is important and urgently needed.

Data to monitor global progress on the goals is critical to keeping countries accountable to their commitments and allows countries to examine how they are doing across multiple, ambitious goals. However, equally important is the rich, granular national and sub-national level data that can guide the development and implementation of evidence-based, effective programs and policies. These kinds of data are also often lacking or of poor quality, in which case more data and better data is essential. But a frequently-ignored piece of the puzzle at the national level is improved use of the data we already have.

Making the most of the data we have

To illustrate this point, consider the Together for Girls partnership, which was built on obtaining new data where it was lacking and effectively translating it into information to change policies and programs. We are a partnership between national governments, UN agencies and private sector organizations working to break cycles of violence, with special attention to sexual violence against girls. …The first pillar of our work is focused on understanding violence against children within a country, always at the request of the national government. We do this through a national household survey – the Violence Against Children Survey (VACS), led by national governments, CDC, and UNICEF as part of the Together for Girls Partnership….

The truth is there is a plethora of data at the country level, generated by surveys, special studies, administrative systems, private sector, and citizens that can provide meaningful insights across all the development goals.

Connecting the dots

But data—like our programs’—often remain in silos. For example, data focused on violence against children is typically not top of mind for those working on women’s empowerment or adolescent health. Yet, as an example, the VACS can offer valuable information about how sexual violence against girls, as young as 13,is connected to adolescent pregnancy—or how one of the most common perpetrators of sexual violence against girls is a partner, a pattern that starts early and is a predictor for victimization and perpetration later in life.  However, these data are not consistently used across actors working on programs related to adolescent pregnancy and violence against women….(More)”.