Stefaan Verhulst
If we really take community and connectedness seriously, we will be vigilant about the extent to which we strengthen or disrupt it when developing health interventions. We will value the knowledge and assets that all people have to offer from their unique relationships with people and place. And ultimately, we will commit to building the power that communities have to create health themselves, beyond clinical services and public health interventions.
Unfortunately, the systems we have created, rather than the solutions we now need, often drive current approaches to improving health. We have garnered from contributors to the series a number of principles to guide us as we develop new ways of doing things, as well as concrete steps toward contributing to a culture that values connections and relationships as much as treatments and health campaigns.
GUIDING PRINCIPLES
- Acknowledge that our success depends on each other. Creating health will happen among individuals and institutions, so we must set aside ego, trust others, and recognize that our individual knowledge is limited and our progress is collective.
- Bring more voices to the table. It is vital to understand the dynamics and relationships within a given community. To do that, we must ensure that all who may be affected by and involved in carrying out an intervention have the opportunity to comfortably share their visions and concerns.
- Expand what counts as knowledge. The insights that communities share often play second fiddle to what professionals and academics typically deem valuable. Putting them on a more equal footing influences what to implement, how to allocate resources, and conclusions about whether something “worked.”
- Embrace emergence, including unpredictability. We must abandon the linear approach favored by traditional health care and embrace the unpredictable nature of community-driven interventions. We must learn and adapt in real time, and remember that unexpected outcomes are one way an intervention can succeed.
- Value what people value. All too often we decide what to aim for and evaluate based on what we can easily measure. It is essential to flip this—to identify goals and then figure out ways of measuring progress toward them. …(More)
New report and dataset by the OECD: “Government at a Glance provides readers with a dashboard of key indicators assembled with the goal of contributing to the analysis and international comparison of public sector performance. Indicators on government revenues, expenditures, and employment are provided alongside key output and outcome data in the sectors of education, health and justice. Government at a Glance also includes indicators on key governance and public management issues, such as transparency in governance, regulatory governance, public procurement and the implementation of employment and remuneration reforms since 2008. While measuring government performance has long been recognized as playing an important role in increasing the effectiveness and efficiency of the public administration, following the economic crisis and fiscal tightening in many member countries, good indicators are needed more than ever to help governments make informed decisions regarding tough choices and help restore confidence in government institutions… (More)”
Kyle Chayka’ in Pacific Standard Magazine:“… The San Francisco-based Neighborly launched in 2013 as a kind of community-based Kickstarter, helping users fund projects close to home. But the site recently pivoted toward presenting a better interface for municipal bonds, highlighting investment opportunities with a slick, Silicon Valley-style interface that makes supporting a local infrastructure project as cool as backing a new model of wrist-wearable computer. It’s bringing innovation to a dusty, though increasingly popular, sector. “You’d be shocked to find how much of the [municipal bonds] process is still being done by email and phone calls,” says Rodrigo Davies, Neighborly’s chief product officer. “This market is really not as modern as you would think.”….Neighborly enters into a gray space between crowdfunding and crowd-investing. The former is what we associate with Kickstarter and Indiegogo, which lump together many small donations into totals that can reach into the millions. In crowdfunding, donations are often made for no guaranteed return. Contrary to what it might suggest, Kickstarter isn’t selling any products; it’s just giving users the opportunity to freely give away money for a legally non-binding promise of a reward, often in the form of a theoretical product. …
Crowd-investing, in contrast, exchanges money for equity in a company, or in Neighborly’s case, a city. Shares of stock or debt purchased through crowd-investing ideally result in profit for the holder, though they can hold as much risk as any vaporware crowdfunding project. But crowd-investing remains largely illegal, despite President Obama’s passing of the JOBS Act in early 2012 that was supposed to clear its path to legitimacy.
The obstacle is that the government’s job is to mitigate the financial risks its citizens can take. That’s why Quire, a start-up that allows fans of popular tech businesses to invest in them themselves, is still only open to “accredited investors,” defined by the government as someone “with income exceeding $200,000 in each of the two most recent years” or who has an individual net worth of over $1 million. Legally, a large investment is categorized as too much risk for anyone under that threshold.
That’s exactly the demographic Neighborly is targeting for municipal bonds, which start in minimum denominations of $5,000. “Bond brokers wouldn’t even look at you unless you have $50-100,000 to invest,” Davies says. The new platform, however, doesn’t discriminate. “We’re looking at people who live in the cities where the projects are happening … in their mid-20s to early 40s, who have some money that they want to invest for the future,” he says. “They put it in a bank savings account or invest it in some funds that they don’t necessarily understand. They should be investing to earn better returns, but they’re not necessarily experienced with financial markets. Those people could benefit a ton from investing in their cities.”…(More)
Anne Russell at Data Science Central: “It’s official. Public concerns over the privacy of data used in digital approaches have reached an apex. Worried about the safety of digital networks, consumers want to gain control over what they increasingly sense as a loss of power over how their data is used. It’s not hard to wonder why. Look at the extent of coverage on the U.S. Government data breach last month and the sheer growth in the number of attacks against government and others overall. Then there is the increasing coverage on the inherent security flaws built into the internet, through which most of our data flows. The costs of data breaches to individuals, industries, and government are adding up. And users are taking note…..
If you’re not sure whether the data fueling your approach will raise privacy and security flags, consider the following. When it comes to data privacy and security, not all data is going to be of equal concern. Much depends on the level of detail in data content, data type, data structure, volume, and velocity, and indeed how the data itself will be used and released.
First there is the data where security and privacy has always mattered and for which there is already an existing and well galvanized body of law in place. Foremost among these is classified or national security data where data usage is highly regulated and enforced. Other data for which there exists a considerable body of international and national law regulating usage includes:
- Proprietary Data – specifically the data that makes up the intellectual capital of individual businesses and gives them their competitive economic advantage over others, including data protected under copyright, patent, or trade secret laws and the sensitive, protected data that companies collect on behalf of its customers;
- Infrastructure Data – data from the physical facilities and systems – such as roads, electrical systems, communications services, etc. – that enable local, regional, national, and international economic activity; and
- Controlled Technical Data – technical, biological, chemical, and military-related data and research that could be considered of national interest and be under foreign export restrictions….
The second group of data that raises privacy and security concerns is personal data. Commonly referred to as Personally Identifiable Information (PII), it is any data that distinguishes individuals from each other. It is also the data that an increasing number of digital approaches rely on, and the data whose use tends to raise the most public ire. …
A third category of data needing privacy consideration is the data related to good people working in difficult or dangerous places. Activists, journalists, politicians, whistle-blowers, business owners, and others working in contentious areas and conflict zones need secure means to communicate and share data without fear of retribution and personal harm. That there are parts of the world where individuals can be in mortal danger for speaking out is one of the reason that TOR (The Onion Router) has received substantial funding from multiple government and philanthropic groups, even at the high risk of enabling anonymized criminal behavior. Indeed, in the absence of alternate secure networks on which to pass data, many would be in grave danger, including those such as the organizers of the Arab Spring in 2010 as well as dissidents in Syria and elsewhere….(More)”
PART ONE: RULEMAKING
Regulators are often the agencies responsible for implementing policy mandates. These mandates can vary from being highly prescriptive to giving regulators great freedom to determine how to implement a policy. In some cases, regulatory agencies have been granted authority by Congress to monitor entire industries, with discretion as to determining how to protect citizens and fair markets.
The business of rulemaking is governed by its own laws and regulations, from the Administrative Procedures Act to approvals of proposed rules by the Office of Management and Budget. All of these processes are designed as a safeguard to protect our citizens while not unduly burdening the regulated businesses or entities.
The process of formal and informal rulemaking is well defined,11incorporates input from citizens and industry, and can take time. Given the challenges previously described, it becomes essential for regulators to think creatively about their rulemaking activities to meet their policy objectives. In this section, we explore several rulemaking opportunities for the regulator of tomorrow:
- Rethinking outreach
- Sensing
- Guidelines and statements versus regulations
- Tomorrow’s talent
- Consultation 2.0…
PART TWO: OVERSIGHT AND ENFORCEMENT
In addition to rulemaking, regulators oversee compliance with the published rules, taking enforcement action when violations occur. Today’s regulators have access to significant amounts of data. Larger data sets combined with increasingly sophisticated analytical tools and the power of the crowd can help regulators better utilize limited resources and reduce the burden of compliance on citizens and business.
This section will explore several oversight and enforcement opportunities for the regulator of tomorrow:
- Correlate to predict
- Citizen as regulator
- Open data
- Collaborative regulating
- Retrospective review…(More)”
Paper by Leonidas G. Anthopoulos: “Smart Cities appeared in literature in late ‘90s and various approaches have been developed so far. Until today, smart city does not describe a city with particular attributes but it is used to describe different cases in urban spaces: web portals that virtualize cities or city guides; knowledge bases that address local needs; agglomerations with Information and Communication Technology (ICT) infrastructure that attract business relocation; metropolitan-wide ICT infrastructures that deliver e-services to the citizens; ubiquitous environments; and recently ICT infrastructure for ecological use. Researchers, practicians, businessmen and policy makers consider smart city from different perspectives and most of them agree on a model that measures urban economy, mobility, environment, living, people and governance. On the other hand, ICT and construction industries stress to capitalize smart city and a new market seems to be generated in this domain. This chapter aims to perform a literature review, discover and classify the particular schools of thought, universities and research centres as well as companies that deal with smart city domain and discover alternative approaches, models, architecture and frameworks with this regard….(More)
Paper by Ansell, Chris; and Torfing, Jacob in Policy & Politics: “Scale is an overlooked issue in the literature on interactive governance. This special issue investigates the challenges posed by the scale and scaling of network and collaborative forms of governance. Our original motivation arose from a concern about whether collaborative governance can scale up. As we learned more, our inquiry expanded to include the tensions inherent in collaboration across scales or at multiple scales and the issue of dynamically scaling collaboration to adapt to changing problems and demands. The diverse cases in this special issue explore these challenges in a range of concrete empirical domains than span the globe…(More)”
Review of Rob Kitchin’s The Data Revolution: Big Data, Open Data, Data Infrastructures & their Consequences by David Moats in Theory, Culture and Society: “…As an industry, academia is not immune to cycles of hype and fashion. Terms like ‘postmodernism’, ‘globalisation’, and ‘new media’ have each had their turn filling the top line of funding proposals. Although they are each grounded in tangible shifts, these terms become stretched and fudged to the point of becoming almost meaningless. Yet, they elicit strong, polarised reactions. For at least the past few years, ‘big data’ seems to be the buzzword, which elicits funding, as well as the ire of many in the social sciences and humanities.
Rob Kitchin’s book The Data Revolution is one of the first systematic attempts to strip back the hype surrounding our current data deluge and take stock of what is really going on. This is crucial because this hype is underpinned by very real societal change, threats to personal privacy and shifts in store for research methods. The book acts as a helpful wayfinding device in an unfamiliar terrain, which is still being reshaped, and is admirably written in a language relevant to social scientists, comprehensible to policy makers and accessible even to the less tech savvy among us.
The Data Revolution seems to present itself as the definitive account of this phenomena but in filling this role ends up adopting a somewhat diplomatic posture. Kitchin takes all the correct and reasonable stances on the matter and advocates all the right courses of action but he is not able to, in the context of this book, pursue these propositions fully. This review will attempt to tease out some of these latent potentials and how they might be pushed in future work, in particular the implications of the ‘performative’ character of both big data narratives and data infrastructures for social science research.
Kitchin’s book starts with the observation that ‘data’ is a misnomer – etymologically data should refer to phenomena in the world which can be abstracted, measured etc. as opposed to the representations and measurements themselves, which should by all rights be called ‘capta’. This is ironic because the worst offenders in what Kitchin calls “data boosterism” seem to conflate data with ‘reality’, unmooring data from its conditions of production and making relationship between the two given or natural.
As Kitchin notes, following Bowker (2005), ‘raw data’ is an oxymoron: data are not so much mined as produced and are necessarily framed technically, ethically, temporally, spatially and philosophically. This is the central thesis of the book, that data and data infrastructures are not neutral and technical but also social and political phenomena. For those at the critical end of research with data, this is a starting assumption, but one which not enough practitioners heed. Most of the book is thus an attempt to flesh out these rapidly expanding data infrastructures and their politics….
Kitchin is at his best when revealing the gap between the narratives and the reality of data analysis such as the fallacy of empiricism – the assertion that, given the granularity and completeness of big data sets and the availability of machine learning algorithms which identify patterns within data (with or without the supervision of human coders), data can “speak for themselves”. Kitchin reminds us that no data set is complete and even these out-of-the-box algorithms are underpinned by theories and assumptions in their creation, and require context specific knowledge to unpack their findings. Kitchin also rightly raises concerns about the limits of big data, that access and interoperability of data is not given and that these gaps and silences are also patterned (Twitter is biased as a sample towards middle class, white, tech savy people). Yet, this language of veracity and reliability seems to suggest that big data is being conceptualised in relation to traditional surveys, or that our population is still the nation state, when big data could helpfully force us to reimagine our analytic objects and truth conditions and more pressingly, our ethics (Rieder, 2013).
However, performativity may again complicate things. As Kitchin observes, supermarket loyalty cards do not just create data about shopping, they encourage particular sorts of shopping; when research subjects change their behaviour to cater to the metrics and surveillance apparatuses built into platforms like Facebook (Bucher, 2012), then these are no longer just data points representing the social, but partially constitutive of new forms of sociality (this is also true of other types of data as discussed by Savage (2010), but in perhaps less obvious ways). This might have implications for how we interpret data, the distribution between quantitative and qualitative approaches (Latour et al., 2012) or even more radical experiments (Wilkie et al., 2014). Kitchin is relatively cautious about proposing these sorts of possibilities, which is not the remit of the book, though it clearly leaves the door open…(More)”