What Government Can and Should Learn From Hacker Culture

Curated on Posted on by Stefaan Verhulst

in The Atlantic: “Can the open-source model work for federal government? Not in every way—for security purposes, the government’s inner workings will never be completely open to the public. Even in the inner workings of government, fears of triggering the next Wikileaks or Snowden scandal may scare officials away from being more open with one another. While not every area of government can be more open, there are a few areas ripe for change.

Perhaps the most glaring need for an open-source approach is in information sharing. Today, among and within several federal agencies, a culture of reflexive and unnecessary information withholding prevails. This knee-jerk secrecy can backfire with fatal consequences, as seen in the 1998 embassy bombings in Africa, the 9/11 attacks, and the Boston Marathon bombings. What’s most troubling is that decades after the dangers of information-sharing were identified, the problem persists.
What’s preventing reform? The answer starts with the government’s hierarchical structure—though an information-is-power mentality and “need to know” Cold War-era culture contribute too. To improve the practice of information sharing, government needs to change the structure of information sharing. Specifically, it needs to flatten the hierarchy.
Former Obama Administration regulation czar Cass Sunstein’s “nudge” approach shows how this could work. In his book Simpler: The Future of Government, he describes how making even small changes to an environment can affect significant changes in behavior. While Sunstein focuses on regulations, the broader lesson is clear: Change the environment to encourage better behavior and people tend to exhibit better behavior. Without such strict adherence to the many tiers of the hierarchy, those working within it could be nudged towards, rather than fight to, share information.
One example of where this worked is in with the State Department’s annual Religious Engagement Report (RER). In 2011, the office in charge of the RER decided that instead of having every embassy submit their data via email, they would post it on a secure wiki. On the surface, this was a decision to change an information-sharing procedure. But it also changed the information-sharing culture. Instead of sharing information only along the supervisor-subordinate axis, it created a norm of sharing laterally, among colleagues.
Another advantage to flattening information-sharing hierarchies is that it reduces the risk of creating “single points of failure,” to quote technology scholar Beth Noveck. The massive amounts of data now available to us may need massive amounts of eyeballs in order to spot patterns of problems—small pools of supervisors atop the hierarchy cannot be expected to shoulder those burdens alone. And while having the right tech tools to share information is part of the solution—as the wiki made it possible for the RER—it’s not enough. Leadership must also create a culture that nudges their staff to use these tools, even if that means relinquishing a degree of their own power.
Finally, a more open work culture would help connect interested parties across government to let them share the hard work of bringing new ideas to fruition. Government is filled with examples of interesting new projects that stall in their infancy. Creating a large pool of collaborators dedicated to a project increases the likelihood that when one torchbearer burns out, others in the agency will pick up for them.
When Linus Torvalds released Linux, it was considered, in Raymond’s words, “subversive” and “a distinct shock.” Could the federal government withstand such a shock?
Evidence suggests it can—and the transformation is already happening in small ways. One of the winners of the Harvard Kennedy School’s Innovations in Government award is State’s Consular Team India (CTI), which won for joining their embassy and four consular posts—each of which used to have its own distinct set of procedures-into a single, more effective unit who could deliver standardized services. As CTI describes it, “this is no top-down bureaucracy” but shares “a common base of information and shared responsibilities.” They flattened the hierarchy, and not only lived, but thrived.”

Open Data Index provides first major assessment of state of open government data

Curated on Posted on by Stefaan Verhulst

Press Release from the Open Knowledge Foundation: “In the week of a major international summit on government transparency in London, the Open Knowledge Foundation has published its 2013 Open Data Index, showing that governments are still not providing enough information in an accessible form to their citizens and businesses.
The UK and US top the 2013 Index, which is a result of community-based surveys in 70 countries. They are followed by Denmark, Norway and the Netherlands. Of the countries assessed, Cyprus, St Kitts & Nevis, the British Virgin Islands, Kenya and Burkina Faso ranked lowest. There are many countries where the governments are less open but that were not assessed because of lack of openness or a sufficiently engaged civil society. This includes 30 countries who are members of the Open Government Partnership.
The Index ranks countries based on the availability and accessibility of information in ten key areas, including government spending, election results, transport timetables, and pollution levels, and reveals that whilst some good progress is being made, much remains to be done.
Rufus Pollock, Founder and CEO of the Open Knowledge Foundation said:

Opening up government data drives democracy, accountability and innovation. It enables citizens to know and exercise their rights, and it brings benefits across society: from transport, to education and health. There has been a welcome increase in support for open data from governments in the last few years, but this Index reveals that too much valuable information is still unavailable.

The UK and US are leaders on open government data but even they have room for improvement: the US for example does not provide a single consolidated and open register of corporations, while the UK Electoral Commission lets down the UK’s good overall performance by not allowing open reuse of UK election data.
There is a very disappointing degree of openness of company registers across the board: only 5 out of the 20 leading countries have even basic information available via a truly open licence, and only 10 allow any form of bulk download. This information is critical for range of reasons – including tackling tax evasion and other forms of financial crime and corruption.
Less than half of the key datasets in the top 20 countries are available to re-use as open data, showing that even the leading countries do not fully understand the importance of citizens and businesses being able to legally and technically use, reuse and redistribute data. This enables them to build and share commercial and non-commercial services.
To see the full results: https://index.okfn.org. For graphs of the data: https://index.okfn.org/visualisations.”

Making government simpler is complicated

Curated on Posted on by Stefaan Verhulst

Mike Konczal in The Washington Post: “Here’s something a politician would never say: “I’m in favor of complex regulations.” But what would the opposite mean? What would it mean to have “simple” regulations?

There are two definitions of “simple” that have come to dominate liberal conversations about government. One is the idea that we should make use of “nudges” in regulation. The other is the idea that we should avoid “kludges.” As it turns out, however, these two definitions conflict with each other —and the battle between them will dominate conversations about the state in the years ahead.

The case for “nudges”

The first definition of a “simple” regulation is one emphasized in Cass Sunstein’s recent book titled Simpler: The Future of Government (also see here). A simple policy is one that simply “nudges” people into one choice or another using a variety of default rules, disclosure requirements, and other market structures. Think, for instance, of rules that require fast-food restaurants to post calories on their menus, or a mortgage that has certain terms clearly marked in disclosures.

These sorts of regulations are deemed “choice preserving.” Consumers are still allowed to buy unhealthy fast-food meals or sign up for mortgages they can’t reasonably afford. The regulations are just there to inform people about their choices. These rules are designed to keep the market “free,” where all possibilities are ultimately possible, although there are rules to encourage certain outcomes.
In his book, however, Sunstein adds that there’s another very different way to understand the term “simple.” What most people mean when they think of simple regulations is a rule that is “simple to follow.” Usually a rule is simple to follow because it outright excludes certain possibilities and thus ensures others. Which means, by definition, it limits certain choices.

The case against “kludges”
This second definition of simple plays a key role in political scientist Steve Teles’ excellent recent essay, “Kludgeocracy in America.” For Teles, a “kludge” is a “clumsy but temporarily effective” fix for a policy problem. (The term comes from computer science.) These kludges tend to pile up over time, making government cumbersome and inefficient overall.
Teles focuses on several ways that kludges are introduced into policy, with a particularly sharp focus on overlapping jurisdictions and the related mess of federal and state overlap in programs. But, without specifically invoking it, he also suggests that a reliance on “nudge” regulations can lead to more kludges.
After all, non-kludge policy proposal is one that will be simple to follow and will clearly cause a certain outcome, with an obvious causality chain. This is in contrast to a web of “nudges” and incentives designed to try and guide certain outcomes.

Why “nudges” aren’t always simpler
The distinction between the two is clear if we take a specific example core to both definitions: retirement security.
For Teles, “one of the often overlooked benefits of the Social Security program… is that recipients automatically have taxes taken out of their paychecks, and, then without much effort on their part, checks begin to appear upon retirement. It’s simple and direct. By contrast, 401(k) retirement accounts… require enormous investments of time, effort, and stress to manage responsibly.”

Yet 401(k)s are the ultimately fantasy laboratory for nudge enthusiasts. A whole cottage industry has grown up around figuring out ways to default people into certain contributions, on designing the architecture of choices of investments, and trying to effortlessly and painlessly guide people into certain savings.
Each approach emphasizes different things. If you want to focus your energy on making people better consumers and market participations, expanding our government’s resources and energy into 401(k)s is a good choice. If you want to focus on providing retirement security directly, expanding Social Security is a better choice.
The first is “simple” in that it doesn’t exclude any possibility but encourages market choices. The second is “simple” in that it is easy to follow, and the result is simple as well: a certain amount of security in old age is provided directly. This second approach understands the government as playing a role in stopping certain outcomes, and providing for the opposite of those outcomes, directly….

Why it’s hard to create “simple” regulations
Like all supposed binaries this is really a continuum. Taxes, for instance, sit somewhere in the middle of the two definitions of “simple.” They tend to preserve the market as it is but raise (or lower) the price of certain goods, influencing choices.
And reforms and regulations are often most effective when there’s a combination of these two types of “simple” rules.
Consider an important new paper, “Regulating Consumer Financial Products: Evidence from Credit Cards,” by Sumit Agarwal, Souphala Chomsisengphet, Neale Mahoney and Johannes Stroebel. The authors analyze the CARD Act of 2009, which regulated credit cards. They found that the nudge-type disclosure rules “increased the number of account holders making the 36-month payment value by 0.5 percentage points.” However, more direct regulations on fees had an even bigger effect, saving U.S. consumers $20.8 billion per year with no notable reduction in credit access…..
The balance between these two approaches of making regulations simple will be front and center as liberals debate the future of government, whether they’re trying to pull back on the “submerged state” or consider the implications for privacy. The debate over the best way for government to be simple is still far from over.”

Google’s flu fail shows the problem with big data

Curated on Posted on by Stefaan Verhulst

Adam Kucharski in The Conversation: “When people talk about ‘big data’, there is an oft-quoted example: a proposed public health tool called Google Flu Trends. It has become something of a pin-up for the big data movement, but it might not be as effective as many claim.
The idea behind big data is that large amount of information can help us do things which smaller volumes cannot. Google first outlined the Flu Trends approach in a 2008 paper in the journal Nature. Rather than relying on disease surveillance used by the US Centers for Disease Control and Prevention (CDC) – such as visits to doctors and lab tests – the authors suggested it would be possible to predict epidemics through Google searches. When suffering from flu, many Americans will search for information related to their condition….
Between 2003 and 2008, flu epidemics in the US had been strongly seasonal, appearing each winter. However, in 2009, the first cases (as reported by the CDC) started in Easter. Flu Trends had already made its predictions when the CDC data was published, but it turned out that the Google model didn’t match reality. It had substantially underestimated the size of the initial outbreak.
The problem was that Flu Trends could only measure what people search for; it didn’t analyse why they were searching for those words. By removing human input, and letting the raw data do the work, the model had to make its predictions using only search queries from the previous handful of years. Although those 45 terms matched the regular seasonal outbreaks from 2003–8, they didn’t reflect the pandemic that appeared in 2009.
Six months after the pandemic started, Google – who now had the benefit of hindsight – updated their model so that it matched the 2009 CDC data. Despite these changes, the updated version of Flu Trends ran into difficulties again last winter, when it overestimated the size of the influenza epidemic in New York State. The incidents in 2009 and 2012 raised the question of how good Flu Trends is at predicting future epidemics, as opposed to merely finding patterns in past data.
In a new analysis, published in the journal PLOS Computational Biology, US researchers report that there are “substantial errors in Google Flu Trends estimates of influenza timing and intensity”. This is based on comparison of Google Flu Trends predictions and the actual epidemic data at the national, regional and local level between 2003 and 2013
Even when search behaviour was correlated with influenza cases, the model sometimes misestimated important public health metrics such as peak outbreak size and cumulative cases. The predictions were particularly wide of the mark in 2009 and 2012:

Original and updated Google Flu Trends (GFT) model compared with CDC influenza-like illness (ILI) data. PLOS Computational Biology 9:10
Click to enlarge

Although they criticised certain aspects of the Flu Trends model, the researchers think that monitoring internet search queries might yet prove valuable, especially if it were linked with other surveillance and prediction methods.
Other researchers have also suggested that other sources of digital data – from Twitter feeds to mobile phone GPS – have the potential to be useful tools for studying epidemics. As well as helping to analysing outbreaks, such methods could allow researchers to analyse human movement and the spread of public health information (or misinformation).
Although much attention has been given to web-based tools, there is another type of big data that is already having a huge impact on disease research. Genome sequencing is enabling researchers to piece together how diseases transmit and where they might come from. Sequence data can even reveal the existence of a new disease variant: earlier this week, researchers announced a new type of dengue fever virus….”

A Data Revolution for Poverty Eradication

Curated on Posted on by Stefaan Verhulst

Report from devint.org: “The High Level Panel on the Post–2015 Development Agenda called for a data revolution for sustainable development, with a new international initiative to improve the quality of statistics and information available to citizens. It recommended actively taking advantage of new technology, crowd sourcing, and improved connectivity to empower people with information on the progress towards the targets. Development Initiatives believes there a number of steps that should be put in place in order to deliver the ambition set out by the Panel.
The data revolution should be seen as a basis on which greater openness and a wider transparency revolution can be built. The openness movement – one of the most exciting and promising developments of the last decade – is starting to transform the citizen-state compact. Rich and developing country governments are adapting the way they do business, recognising that greater transparency and participation leads to more effective, efficient, and equitable management of scarce public resources. Increased openness of data has potential to democratise access to information, empowering individuals with the knowledge they need to tackle the problems that they face. To realise this bold ambition, the revolution will need to reach beyond the niche data and statistical communities, sell the importance of the revolution to a wide range of actors (governments, donors, CSOs and the media) and leverage the potential of open data to deliver more usable information”

You Can Predict What Government Agencies Will Buy; For Real!

Curated on Posted on by Stefaan Verhulst

Jen Clement at GovLoop: “Two great free government-run websites that show how federal government agencies are spending their money are USASpending.gov and FedBizOpps.gov. Each site allows you to research how the government has spent its procurement dollars in the last several years, and can give business owners a snapshot of what industry segments and what type of commercial products and services offer the best contracting opportunities so vendors can conduct their target business analysis and approach a select group of potential buyers.

SmartProcure offers a unique service that allows you to search thousands and thousands of government purchase orders, providing you ability to predict purchasing opportunity in the future. SmartProcure lets you search specifically for a product or service you sell and show you exactly which government agencies have bought that product or service, how much they paid, and which vendors (your competitors) they’ve purchased from. In addition to purchasing histories you’ll have access to powerful market analysis tools to help you conduct thorough competitive and market intelligence reviews to find the right niches for your business to take advantage of.  Whether it is federal, state, or local governments, a snapshot into the past can help determine the future…
For more helpful tips visit:  https://ow133.infusionsoft.com/go/blog/jc/ ”

And Data for All: On the Validity and Usefulness of Open Government Data

Curated on Posted on by Stefaan Verhulst

Paper presented at the the 13th International Conference on Knowledge Management and Knowledge Technologies: “Open Government Data (OGD) stands for a relatively young trend to make data that is collected and maintained by state authorities available for the public. Although various Austrian OGD initiatives have been started in the last few years, less is known about the validity and the usefulness of the data offered. Based on the data-set on Vienna’s stock of trees, we address two questions in this paper. First of all, we examine the quality of the data by validating it according to knowledge from a related discipline. It shows that the data-set we used correlates with findings from meteorology. Then, we explore the usefulness and exploitability of OGD by describing a concrete scenario in which this data-set can be supportive for citizens in their everyday life and by discussing further application areas in which OGD can be beneficial for different stakeholders and even commercially used.”

Seven Principles for Big Data and Resilience Projects

Curated on Posted on by Stefaan Verhulst

PopTech & Rockefeler Bellagio Fellows: “The following is a draft “Code of Conduct” that seeks to provide guidance on best practices for resilience building projects that leverage Big Data and Advanced Computing. These seven core principles serve to guide data projects to ensure they are socially just, encourage local wealth- & skill-creation, require informed consent, and be maintainable over long timeframes. This document is a work in progress, so we very much welcome feedback. Our aim is not to enforce these principles on others but rather to hold ourselves accountable and in the process encourage others to do the same. Initial versions of this draft were written during the 2013 PopTech & Rockefeller Foundation workshop in Bellagio, August 2013.
Open Source Data Tools – Wherever possible, data analytics and manipulation tools should be open source, architecture independent and broadly prevalent (R, python, etc.). Open source, hackable tools are generative, and building generative capacity is an important element of resilience….
Transparent Data Infrastructure – Infrastructure for data collection and storage should operate based on transparent standards to maximize the number of users that can interact with the infrastructure. Data infrastructure should strive for built-in documentation, be extensive and provide easy access. Data is only as useful to the data scientist as her/his understanding of its collection is correct…
Develop and Maintain Local Skills – Make “Data Literacy” more widespread. Leverage local data labor and build on existing skills. The key and most constraint ingredient to effective data solutions remains human skill/knowledge and needs to be retained locally. In doing so, consider cultural issues and language. Catalyze the next generation of data scientists and generate new required skills in the cities where the data is being collected…
Local Data Ownership – Use Creative Commons and licenses that state that data is not to be used for commercial purposes. The community directly owns the data it generates, along with the learning algorithms (machine learning classifiers) and derivatives. Strong data protection protocols need to be in place to protect identities and personally identifying information…
Ethical Data Sharing – Adopt existing data sharing protocols like the ICRC’s (2013). Permission for sharing is essential. How the data will be used should be clearly articulated. An opt in approach should be the preference wherever possible, and the ability for individuals to remove themselves from a data set after it has been collected must always be an option. Projects should always explicitly state which third parties will get access to data, if any, so that it is clear who will be able to access and use the data…
Right Not To Be Sensed – Local communities have a right not to be sensed. Large scale city sensing projects must have a clear framework for how people are able to be involved or choose not to participate. All too often, sensing projects are established without any ethical framework or any commitment to informed consent. It is essential that the collection of any sensitive data, from social and mobile data to video and photographic records of houses, streets and individuals, is done with full public knowledge, community discussion, and the ability to opt out…
Learning from Mistakes – Big Data and Resilience projects need to be open to face, report, and discuss failures. Big Data technology is still very much in a learning phase. Failure and the learning and insights resulting from it should be accepted and appreciated. Without admitting what does not work we are not learning effectively as a community. Quality control and assessment for data-driven solutions is notably harder than comparable efforts in other technology fields. The uncertainty about quality of the solution is created by the uncertainty inherent in data…”

Five Ways to Make Government Procurement Better

Curated on Posted on by Stefaan Verhulst

Mark Headd at Civic Innovations:  “Nothing in recent memory has focused attention on the need for wholesale reform of the government IT procurement system more than the troubled launch of healthcare.gov.
There has been a myriad of blog posts, stories and articles written in the last few weeks detailing all of the problems that led to the ignominious launch of the website meant to allow people to sign up for health care coverage.
Though the details of this high profile flop are in the latest headlines, the underlying cause has been talked about many times before – the process by which governments contract with outside parties to obtain IT services is broken…
With all of this in mind, here are – in no particular order – five suggested changes that can be adopted to improve the government procurement process.
Raise the threshold on simplified / streamlined procurement
Many governments use a separate, more streamlined process for smaller projects that do not require a full RFP (in the City of Philadelphia, professional services projects that do not exceed $32,000 annually go through this more streamlined bidding process). In Philadelphia, we’ve had great success in using these smaller projects to test new ideas and strategies for partnering with IT vendors. There is much we can learn from these experiments, and a modest increase to enable more experimentation would allow governments to gain valuable new insights.
Narrowing the focus of any enhanced thresholds for streamlined budding to web-based projects would help mitigate risk and foster a quicker process for testing new ideas.
Identify clear standards for projects
Having a clear set of vendor-agnostic IT standards to use when developing RFPs and in performing work can make a huge difference in how a project turns out. Clearly articulating standards for:

  • The various components that a system will use.
  • The environment in which it will be housed.
  • The testing it must undergo prior to final acceptance.

…can go a long way to reduce the risk an uncertainly inherent in IT projects.
It’s worth noting that most governments probably already have a set of IT standards that are usually made part of any IT solicitation. But these standards documents can quickly become out of date – they must undergo constant review and refinement. In addition, many of the people writing these standards may confuse a specific vendor product or platform with a true standard.
Require open source
Requiring that IT projects be open source during development or after completion can be an effective way to reduce risk on an IT project and enhance transparency. This is particularly true of web-based projects.
In addition, government RFPs should encourage the use of existing open source tools – leveraging existing software components that are in use in similar projects and maintained by an active community – to foster external participation by vendors and volunteers alike. When governments make the code behind their project open source, they enable anyone that understands software development to help make them better.
Develop a more robust internal capacity for IT project management and implementation
Governments must find ways to develop the internal capacity for developing, implementing and managing technology projects.
Part of the reason that governments make use of a variety of different risk mitigation provisions in public bidding is that there is a lack of people in government with hands on experience building or maintaining technology. There is a dearth of makers in government, and there is a direct relationship between the perceived risk that governments take on with new technology projects and the lack of experienced technologists working in government.
Governments need to find ways to develop a maker culture within their workforces and should prioritize recruitment from the local technology and civic hacking communities.
Make contracting, lobbying and campaign contribution data public as open data
One of the more disheartening revelations to come out of the analysis of healthcare.gov implementation is that some of the firms that were awarded work as part of the project also spent non-trivial amounts of money on lobbying. It’s a good bet that this kind of thing also happens at the state and local level as well.
This can seriously undermine confidence in the bidding process, and may cause many smaller firms – who lack funds or interest in lobbying elected officials – to simply throw up their hands and walk away.
In the absence of statutory or regulatory changes to prevent this from happening, governments can enhance the transparency around the bidding process by working to ensure that all contracting data as well as data listing publicly registered lobbyists and contributions to political campaigns is open.
Ensuring that all prospective participants in the public bidding process have confidence that the process will be fair and transparent is essential to getting as many firms to participate as possible – including small firms more adept at agile software development methodologies. More bids typically equates to higher quality proposals and lower prices.
None of the changes list above will be easy, and governments are positioned differently in how well they may achieve any one of them. Nor do they represent the entire universe of things we can do to improve the system in the near term – these are items that I personally think are important and very achievable.
One thing that could help speed the adoption of these and other changes is the development of robust communication framework between government contracting and IT professionals in different cities and different states. I think a “Municipal Procurement Academy” could go a long way toward achieving this.”

Democracy and Political Ignorance

Curated on Posted on by Stefaan Verhulst

Essay by Ilya Somin in Special issue on Is Smaller Government Smarter Government? of Cato Unbound: ” Democracy is supposed to be rule of the people, by the people, and for the people. But in order to rule effectively, the people need political knowledge. If they know little or nothing about government, it becomes difficult to hold political leaders accountable for their performance. Unfortunately, public knowledge about politics is disturbingly low. In addition, the public also often does a poor job of evaluating the political information they do know. This state of affairs has persisted despite rising education levels, increased availability of information thanks to modern technology, and even rising IQ scores. It is mostly the result of rational behavior, not stupidity. Such widespread and persistent political ignorance and irrationality strengthens the case for limiting and decentralizing the power of government….
Political ignorance in America is deep and widespread. The current government shutdown fight provides some good examples. Although Obamacare is at the center of that fight and much other recent political controversy, 44% percent of the public do not even realize it is still the law. Some 80 percent, according to a recent Kaiser survey, say they have heard “nothing at all” or “only a little” about the controversial insurance exchanges that are a major part of the law….
Some people react to data like the above by thinking that the voters must be stupid. Butpolitical ignorance is actually rational for most of the public, including most smart people. If your only reason to follow politics is to be a better voter, that turns out not be much of a reason at all. That is because there is very little chance that your vote will actually make a difference to the outcome of an election (about 1 in 60 million in a presidential race, for example).2 For most of us, it is rational to devote very little time to learning about politics, and instead focus on other activities that are more interesting or more likely to be useful. As former British Prime Minister Tony Blair puts it, “[t]he single hardest thing for a practising politician to understand is that most people, most  of the time, don’t give politics a first thought all day long. Or if they do, it is with a sigh…. before going back to worrying about the kids, the parents, the mortgage, the boss, their friends, their weight, their health, sex and rock ‘n’ roll.”3 Most people don’t precisely calculate the odds that their vote will make a difference. But they probably have an intuitive sense that the chances are very small, and act accordingly.
In the book, I also consider why many rationally ignorant people often still bother to vote.4 The key factor is that voting is a lot cheaper and less time-consuming than studying political issues. For many, it is rational to take the time to vote, but without learning much about the issues at stake….
Political ignorance is far from the only factor that must be considered in deciding the appropriate size, scope, and centralization of government. For example, some large-scale issues, such as global warming, are simply too big to be effectively addressed by lower-level governments or private organizations. Democracy and Political Ignorance is not a complete theory of the proper role of government in society. But it does suggest that the problem of political ignorance should lead us to limit and decentralize government more than we would otherwise.”
See also:  Ilya Somin, Democracy and Political Ignorance: Why Smaller Government is Smarter, (Stanford: Stanford University Press, 2013)