Could a tweet or a text increase college enrollment or student achievement?

Curated on Posted on by Stefaan Verhulst

 at the Conversation: “Can a few text messages, a timely email or a letter increase college enrollment and student achievement? Such “nudges,” designed carefully using behavioral economics, can be effective.

But when do they work – and when not?

Barriers to success

Consider students who have just graduated high school intending to enroll in college. Even among those who have been accepted to college, 15 percent of low-income students do not enroll by the next fall. For the large share who intend to enroll in community colleges, this number can be as high as 40 percent….

Can a few text messages or a timely email overcome these barriers? My research uses behavioral economics to design low-cost, scalable interventions aimed at improving education outcomes. Behavioral economics suggests several important features to make a nudge effective: simplify complex information, make tasks easier to complete and ensure that support is timely.

So, what makes for an effective nudge?

Improving college enrollment

In 2012, researchers Ben Castleman and Lindsay Page sent 10 text messages to nearly 2,000 college-intending students the summer after high school graduation. These messages provided just-in-time reminders on key financial aid, housing and enrollment deadlines from early July to mid August.

Instead of set meetings with counselors, students could reply to messages and receive on-demand support from college guidance counselors to complete key tasks.

In another intervention – the Expanding College Opportunities Project (ECO) – researchers Caroline Hoxby and Sarah Turner worked to help high-achieving, low-income students enroll in colleges on par with their achievement. The intervention arrived to students as a packet in the mail.

The mailer simplified information by providing a list of colleges tailored to each student’s location along with information about net costs, graduation rates, and application deadlines. Moreover, the mailer included easy-to-claim application fee waivers. All these features reduced both the complexity and cost in applying to a wider range of colleges.

In both cases, researchers found that it significantly improved college outcomes. College enrollment went up by 15 percent in the intervention designed to reduce summer melt for community college students. The ECO project increased the likelihood of admission to a selective college by 78 percent.

…

When there is no impact

While these interventions are promising, there are important caveats.

For instance, our preliminary findings from ongoing research show that information alone may not be enough. We sent emails and letters to more than one hundred thousand college applicants about financial aid and education-related tax benefits. However, we didn’t provide any additional support to help families through the process of claiming these benefits.

In other words, we didn’t provide any support to complete the tasks – no fee waivers, no connection to guidance counselors – just the email and the letter. Without this support to answer questions or help families complete forms to claim the benefits, we found no impact, even when students opened the emails.

More generally, “nudges” often lead to modest impacts and should be considered only a part of the solution. But there’s a dearth of low-cost, scalable interventions in education, and behavioral economics can help.

Identifying the crucial decision points – when applications are due, forms need to be filled out or school choices are made – and supplying the just-in-time support to families is key….(More).”

Moneyballing Criminal Justice

Curated on Posted on by Stefaan Verhulst

Anne Milgram in the Atlantic: “…One area in which the potential of data analysis is still not adequately realized,however, is criminal justice. This is somewhat surprising given the success of CompStat, a law enforcement management tool that uses data to figure out how police resources can be used to reduce crime and hold law enforcement officials accountable for results. CompStat is widely credited with contributing to New York City’s dramatic reduction in serious crime over the past two decades. Yet data-driven decision-making has not expanded to the whole of the criminal justice system.

But it could. And, in this respect, the front end of the system — the part of the process that runs from arrest through sentencing — is particularly important. Atthis stage, police, prosecutors, defenders, and courts make key choices about how to deal with offenders — choices that, taken together, have an enormous impact on crime. Yet most jurisdictions do not collect or analyze the data necessary to know whether these decisions are being made in a way that accomplishes the most important goals of the criminal justice system: increased public safety,decreased recidivism, reduced cost, and the fair, efficient administration of justice.

Even in jurisdictions where good data exists, a lack of technology is often an obstacle to using it effectively. Police, jails, courts, district attorneys, and public defenders each keep separate information systems, the data from which is almost never pulled together and analyzed in a way that could answer the questions that matter most: Who is in our criminal justice system? What crimes have been charged? What risks do individual offenders pose? And which option would best protect the public and make the best use of our limited resources?

While debates about prison over-crowding, three strikes laws, and mandatory minimum sentences have captured public attention, the importance of what happens between arrest and sentencing has gone largely unnoticed. Even though I ran the criminal justice system in New Jersey, one of the largest states in the country, I had not realized the magnitude of the pretrial issues until I was tasked by theLaura and John Arnold Foundation with figuring out which aspects of criminal justice had the most need and presented the greatest opportunity for reform….

Technology could help us leverage data to identify offenders who will pose unacceptable risks to society if they are not behind bars and distinguish them from those defendants who will have lower recidivism rates if they are supervised in the community or given alternatives to incarceration before trial. Likewise, it could help us figure out which terms of imprisonment, alternatives to incarceration, and other interventions work best–and for whom. And the list does not end there.

The truth is our criminal justice system already makes these decisions every day.But it makes them without knowing whether they’re the right ones. That needs to change. If data is powerful enough to transform baseball, health care, and education, it can do the same for criminal justice….(More)”

…(More).

Workplace innovation in the public sector

Curated on Posted on by Stefaan Verhulst

Eurofound: “Innovative organisational practices in the workplace, which aim to make best use of human capital, are traditionally associated with the private sector. The nature of the public sector activities makes it more difficult to identify these types of internal innovation in publicly funded organisations.

It is widely thought that public sector organisations are neither dynamic nor creative and are typified by a high degree of inertia. Yet the necessity of innovation ought not to be dismissed. The public sector represents a quarter of total EU employment, and it is of critical importance as a provider and regulator of services. Improving how it performs has a knock-on effect not only for private sector growth but also for citizens’ satisfaction. Ultimately, this improves governance itself.

So how can innovative organisation practices help in dealing with the challenges faced by the public sector? Eurofound, as part of a project on workplace innovation in European companies, carried out case studies of both private and public sector organisations. The findings show a number of interesting practices and processes used.

Employee participation

The case studies from the public sector, some of which are described below, demonstrate the central role of employee participation in the implementation of workplace innovation and its impacts on organisation and employees. They indicate that innovative practices have resulted in enhanced organisational performance and quality of working life.

It is widely thought that changes in the public sector are initiated as a response to government policies. This is often true, but workplace innovation may also be introduced as a result of well-designed initiatives driven by external pressures (such as the need for a more competitive public service) or internal pressures (such as a need to update the skills map to better serve the public).

Case study findings

The state-owned Lithuanian energy company Lietuvos Energijos Gamyba (140 KB PDF) encourages employee participation by providing a structured framework for all employees to propose improvements. This has required a change in managerial approach and has spread a sense of ownership horizontally and vertically in the company. The Polish public transport company Jarosław City Transport (191 KB PDF), when faced with serious financial stability challenges, as well as implementing operational changes, set up ways for employees’ voices to be heard, which enabled a contributory dialogue and strengthened partnerships. Consultation, development of mutual trust, and common involvement ensured an effective combination of top-down and bottom-up initiatives.

The Lithuanian Post, AB Lietuvos Pastas (136 KB PDF) experienced a major organisation transformation in 2010 to improve efficiency and quality of service. Through a programme of ‘Loyalty day’ monthly visits, both top and middle management of the central administration visit any part of the company and work with colleagues in other units. Under budgetary pressure to ‘earn their money’, the Danish Vej and Park Bornholm (142 KB PDF) construction services in roads, parks and forests had to find innovative solutions to deal with a merger and privatisation. Their intervention had the characteristics of workplace partnership with a new set of organisational values set from the bottom up. Self-managing teams are essential for the operation of the company.

The world of education has provided new structures that provide better outcomes for students. The South West University of Bulgaria (214 KB PDF) also operates small self-managing teams responsible for employee scheduling. Weekly round-tables encourage participation in collectively finding solutions, creating a more effective environment in which to respond to the competitive demands of education provision.

In Poland, an initiative by the Pomeranian Library (185 KB PDF) improved employee–management dialogue and communication through increased participation. The initiative is a response to the new frameworks for open access to knowledge for users, with the library mirroring the user experience through its own work practices.

Through new dialogue, government advisory bodies have also developed employee-led improvement. Breaking away from a traditional hierarchy is considered important in achieving a more flexible work organisation. Under considerable pressure, the top-heavy management of the British Geological Survey (89 KB PDF) now operates a flexible matrix that promotes innovative and entrepreneurial ways of working. And in Germany, Niersverband (138 KB PDF), a publicly owned water-management company innovated through training, learning, reflection partnerships and workplace partnerships. New occupational profiles were developed to meet external demands. Based on dialogue concerning workplace experiences and competences, employees acquired new qualifications that allowed the company to be more competitive.

In the Funen Village Museum in Odense, Denmark, (143 KB PDF) innovation came about at the request of staff looking for more flexibility in how they work. Formerly most of their work was maintenance tasks, but now they can now engage more with visitors. Control of schedules has moved to the team rather than being the responsibility of a single manager. As a result, museum employees are now hosts as well as craftspeople. They no longer feel ‘forgotten’ and are happier in their work….(More)”

The report Workplace innovation in European companies provides a full analysis of the case studies.

The 51 case studies and the  list of companies (PDF 119 KB) the case studies are based on are available for download.

Fifty Shades of Open

Curated on Posted on by Stefaan Verhulst

Jeffrey Pomerantz and Robin Peek at First Monday: “Open source. Open access. Open society. Open knowledge. Open government. Even open food. Until quite recently, the word “open” had a fairly constant meaning. The over-use of the word “open” has led to its meaning becoming increasingly ambiguous. This presents a critical problem for this important word, as ambiguity leads to misinterpretation.

“Open” has been applied to a wide variety of words to create new terms, some of which make sense, and some not so much. When we started writing this essay, we thought our working title was simply amusing. But the working title became the actual title, as we found that there are at least 50 different terms in which the word “open” is used, encompassing nearly as many different criteria for openness. In this essay we will attempt to make sense of this open season on the word “open.”

Opening the door on open

The word “open” is, perhaps unsurprisingly, a very old one in the English language, harking back to Early Old English. Unlike some words in English, the definition of “open” has changed very little in the intervening thousand-plus years: the earliest recorded uses of the word are completely consistent with its modern usage as an adjective, indicating a passage through or an access into something (Oxford English Dictionary, 2016).

This meaning leads to the development in the fifteenth century of the phrases “open house,” meaning an establishment in which all are welcome, and “open air,” meaning unenclosed outdoor spaces. One such unenclosed outdoor space that figured large in the fifteenth century, and continues to do so today, is the Commons (Hardin, 1968): land or other resources that are not privately owned, but are available for use to all members of a community. The word “open” in these phrases indicates that all have access to a shared resource. All are welcome to visit an open house, but not to move in; all are welcome to walk in the open air or graze their sheep on the Commons, but not to fence the Commons as part of their backyard. (And the moment at which Commons land ceases to be open is precisely the moment it is fenced by an owner, which is in fact what happened in Great Britain during the Enclosure movement of the sixteenth through eighteenth centuries.)

Running against the grain of this cultural movement to enclosure, the nineteenth century saw the circulating library become the norm — rather than libraries in which massive tomes were literally chained to desks. The interpretation of the word “open” to mean a shared resource to which all had access, fit neatly into the philosophy of the modern library movement of the nineteenth century. The phrases “open shelves” and “open stacks” emerged at this time, referring to resources that were directly available to library users, without necessarily requiring intervention by a librarian. Naturally, however, not all library resources were made openly available, nor are they even today. Furthermore, resources are made openly available with the understanding that, like Commons land, they must be shared: library resources have a due date.

The twentieth century saw an increase in the use of the word “open,” as well as a hint of the confusion that was to come about the interpretation of the word. The term “open society” was coined prior to World War I, to indicate a society tolerant of religious diversity. The “open skies” policy enables a nation to allow other nations’ commercial aviation to fly through its airspace — though, importantly, without giving up control of its airspace. The Open University was founded in the United Kingdom in 1969, to provide a university education to all, with no formal entry requirements. The meaning of the word “open” is quite different across these three terms — or perhaps it would be more accurate to say that these terms use different shadings of the word.

But it has been the twenty-first century that has seen the most dramatic increase in the number of terms that use “open.” The story of this explosion in the use of the word “open” begins, however, with a different word entirely: the word “free.”….

Introduction
Opening the door on open
Speech, beer, and puppies
Open means rights
Open means access
Open means use
Open means transparent
Open means participatory
Open means enabling openness
Open means philosophically aligned with open principles
Openwashing and its discontents
Conclusion“

‘Big data’ was supposed to fix education. It didn’t. It’s time for ‘small data’

Curated on Posted on by Stefaan Verhulst

Pasi Sahlberg and Jonathan Hasak in the Washington Post: “One thing that distinguishes schools in the United States from schools around the world is how data walls, which typically reflect standardized test results, decorate hallways and teacher lounges. Green, yellow, and red colors indicate levels of performance of students and classrooms. For serious reformers, this is the type of transparency that reveals more data about schools and is seen as part of the solution to how to conduct effective school improvement. These data sets, however, often don’t spark insight about teaching and learning in classrooms; they are based on analytics and statistics, not on emotions and relationships that drive learning in schools. They also report outputs and outcomes, not the impacts of learning on the lives and minds of learners….

If you are a leader of any modern education system, you probably care a lot about collecting, analyzing, storing, and communicating massive amounts of information about your schools, teachers, and students based on these data sets. This information is “big data,” a term that first appeared around 2000, which refers to data sets that are so large and complex that processing them by conventional data processing applications isn’t possible. Two decades ago, the type of data education management systems processed were input factors of education system, such as student enrollments, teacher characteristics, or education expenditures handled by education department’s statistical officer. Today, however, big data covers a range of indicators about teaching and learning processes, and increasingly reports on student achievement trends over time.

With the outpouring of data, international organizations continue to build regional and global data banks. Whether it’s the United Nations, the World Bank, the European Commission, or the Organization for Economic Cooperation and Development, today’s international reformers are collecting and handling more data about human development than before. Beyond government agencies, there are global education and consulting enterprises like Pearson and McKinsey that see business opportunities in big data markets.

Among the best known today is the OECD’s Program for International Student Assessment (PISA), which measures reading, mathematical, and scientific literacy of 15-year-olds around the world. OECD now also administers an Education GPS, or a global positioning system, that aims to tell policymakers where their education systems place in a global grid and how to move to desired destinations. OECD has clearly become a world leader in the big data movement in education.

Despite all this new information and benefits that come with it, there are clear handicaps in how big data has been used in education reforms. In fact, pundits and policymakers often forget that Big data, at best, only reveals correlations between variables in education, not causality. As any introduction to statistics course will tell you, correlation does not imply causation….
We believe that it is becoming evident that big data alone won’t be able to fix education systems. Decision-makers need to gain a better understanding of what good teaching is and how it leads to better learning in schools. This is where information about details, relationships and narratives in schools become important. These are what Martin Lindstrom calls “small data”: small clues that uncover huge trends. In education, these small clues are often hidden in the invisible fabric of schools. Understanding this fabric must become a priority for improving education.

To be sure, there is not one right way to gather small data in education. Perhaps the most important next step is to realize the limitations of current big data-driven policies and practices. Too strong reliance on externally collected data may be misleading in policy-making. This is an example of what small data look like in practice:

  • It reduces census-based national student assessments to the necessary minimum and transfer saved resources to enhance the quality of formative assessments in schools and teacher education on other alternative assessment methods. Evidence shows that formative and other school-based assessments are much more likely to improve quality of education than conventional standardized tests.
  • It strengthens collective autonomy of schools by giving teachers more independence from bureaucracy and investing in teamwork in schools. This would enhance social capital that is proved to be critical aspects of building trust within education and enhancing student learning.
  • It empowers students by involving them in assessing and reflecting their own learning and then incorporating that information into collective human judgment about teaching and learning (supported by national big data). Because there are different ways students can be smart in schools, no one way of measuring student achievement will reveal success. Students’ voices about their own growth may be those tiny clues that can uncover important trends of improving learning.

Edwards Deming once said that “without data you are another person with an opinion.” But Deming couldn’t have imagined the size and speed of data systems we have today….(More)”

Big Risks, Big Opportunities: the Intersection of Big Data and Civil Rights

Curated on Posted on by Stefaan Verhulst

Latest White House report on Big Data charts pathways for fairness and opportunity but also cautions against re-encoding bias and discrimination into algorithmic systems: ” Advertisements tailored to reflect previous purchasing decisions; targeted job postings based on your degree and social networks; reams of data informing predictions around college admissions and financial aid. Need a loan? There’s an app for that.

As technology advances and our economic, social, and civic lives become increasingly digital, we are faced with ethical questions of great consequence. Big data and associated technologies create enormous new opportunities to revisit assumptions and instead make data-driven decisions. Properly harnessed, big data can be a tool for overcoming longstanding bias and rooting out discrimination.

The era of big data is also full of risk. The algorithmic systems that turn data into information are not infallible—they rely on the imperfect inputs, logic, probability, and people who design them. Predictors of success can become barriers to entry; careful marketing can be rooted in stereotype. Without deliberate care, these innovations can easily hardwire discrimination, reinforce bias, and mask opportunity.

Because technological innovation presents both great opportunity and great risk, the White House has released several reports on “big data” intended to prompt conversation and advance these important issues. The topics of previous reports on data analytics included privacy, prices in the marketplace, and consumer protection laws. Today, we are announcing the latest report on big data, one centered on algorithmic systems, opportunity, and civil rights.

The first big data report warned of “the potential of encoding discrimination in automated decisions”—that is, discrimination may “be the inadvertent outcome of the way big data technologies are structured and used.” A commitment to understanding these risks and harnessing technology for good prompted us to specifically examine the intersection between big data and civil rights.

Using case studies on credit lending, employment, higher education, and criminal justice, the report we are releasing today illustrates how big data techniques can be used to detect bias and prevent discrimination. It also demonstrates the risks involved, particularly how technologies can deliberately or inadvertently perpetuate, exacerbate, or mask discrimination.

The purpose of the report is not to offer remedies to the issues it raises, but rather to identify these issues and prompt conversation, research—and action—among technologists, academics, policy makers, and citizens, alike.

The report includes a number of recommendations for advancing work in this nascent field of data and ethics. These include investing in research, broadening and diversifying technical leadership, cross-training, and expanded literacy on data discrimination, bolstering accountability, and creating standards for use within both the government and the private sector. It also calls on computer and data science programs and professionals to promote fairness and opportunity as part of an overall commitment to the responsible and ethical use of data.

Big data is here to stay; the question is how it will be used: to advance civil rights and opportunity, or to undermine them….(More)”

Opening up census data for research

Curated on Posted on by Stefaan Verhulst

Economic and Social Research Council (UK): “InFuse, an online search facility for census data, is enabling tailored search and investigation of UK census statistics – opening new opportunities for aggregating and comparing population counts.

Impacts

  • InFuse data were used for the ‘Smarter Travel’ research project studying how ‘smart choices’ for sustainable travel could be implemented and supported in transport planning. The research directly influenced UK climate-change agendas and policy, including:
    • the UK Committee on Climate Change recommendations on cost-effective-emission reductions
    • the Scottish Government’s targets and household advice for smarter travel
    • the UK Government’s Local Sustainable Transport Fund supporting 96 projects across England
    • evaluations for numerous Local Authority Transport Plans across the UK.
  • The Integration Hub, a web resource that was launched by Demos in 2015 to provide data about ethnic integration in England and Wales, uses data from InFuse to populate its interactive maps of the UK.
  • Census data downloaded from InFuse informed the Welsh Government for policies to engage Gypsy and Traveller families in education, showing that over 60 per cent aged over 16 from these communities had no qualifications.
  • Executive recruitment firm Sapphire Partners used census data from InFuse in a report on female representation on boards, revealing that 77 per cent of FTSE board members are men, and 70 per cent of new board appointments go to men.
  • A study by the Marie Curie charity into the differing needs of Black, Asian and minority ethnic groups in Scotland for end-of-life care used InFuse to determine that the minority ethnic population in Scotland has doubled since 2001 from 100,000 to 200,000 – highlighting the need for greater and more appropriate provision.
  • A Knowledge Transfer Partnership between homelessness charity Llamau and Cardiff University used InFuse data to show that Welsh young homeless people participating in the study were over twice as likely to have left school with no qualifications compared to UK-wide figures for their age group and gender….(More)”

 

From Stalemate to Solutions

Curated on Posted on by Stefaan Verhulst

Karen Abrams Gerber & Andrea Jacobs  at Stanford Social Innovation Review: “….We waste time asking, “How can we change the way people think?” when we should be asking, “How do we change the way we do things?”

Changing how we do things isn’t just about reworking laws, policies, and systems; it means rethinking the very act of problem-solving. We believe there are five basic tenets to successful collaboration:

  1. Engaging unlikely bedfellows
  2. Creating a resonant vision
  3. Cultivating relationships
  4. Communicating across worldviews
  5. Committing to ongoing learning

Over the past two years, we’ve researched an organization that embodies all of these: Convergence Center for Policy Resolution “convenes people and groups with conflicting views to build trust, identify solutions, and form alliances for action on critical national issues.” Its projects include reimagining K-12 education, addressing economic mobility and poverty, reforming the federal budget process, financing long-term care, and improving the dietary choices and wellness of Americans.

The organization’s unique approach to collaboration enables adversaries to work together and develop breakthrough solutions. It starts with targeting and framing an issue, and then enrolling a wide spectrum of stakeholders. Over an extended period of time, these stakeholders attend a series of expertly facilitated meetings to explore the issue and identify solutions, and finally take joint action….

Foundational to Convergence’s success is the principle of engaging unlikely bedfellows. Stakeholder diversity helps eliminate the “echo chamber” effect (also described by Witter and Mikulsky) created when like-minded groups talk only with one another. The organization vets potential stakeholders to determine their capacity for working with the tensions and complexities of diverse perspectives and their willingness to participate in an emergent process, believing that each ideological camp holds a crucial piece of the puzzle and that the tension of differing views actually creates better solutions.

Convergence exemplifies the power of creating a resonant vision in its approach to tackling big social issues. Framing the issue in a way that galvanizes all stakeholders takes tremendous time, energy, and skill. For example, when the organization decided to focus on addressing K-12 education in the United States, it engaged in hundreds of interviews to identify the best way to frame the project. While everyone agreed the system did not serve the needs of many students, they had difficulty finding consensus about how to move forward. One stakeholder commented that the current system was based on a 19th-century factory model that could never meet the needs of 21st-century students. This comment sparked a new narrative that excited stakeholders across the ideological spectrum: “reimagining education for the 21st century!”

It’s important to note that Convergence focuses on framing the problem, not formulating the solution(s). Rather, it believes the solution emerges through the process of authentic collaboration. This differs significantly from an advocacy-based approach, in which a group agrees on a solution and then mobilizes as much support for that solution as possible. As a result, solutions created through Convergence’s collaborative approach are better able to weather the resistance that all change efforts face, because some of that resistance is built into the process.

Change takes time, and so does cultivating relationships. In an article last year, Jane Wei-Skillern, David Ehrlichman, and David Sawyer wrote, “The single most important factor behind all successful collaborations is trust-based relationships among participants.”…..

Change is complex and certainly not linear. Convergence’s approach “lives” this complexity and uncertainty. In its own words, the organization is “building the ship while sailing it.” Its success is due in part to actively and simultaneously engaging each of the five tenets of authentic collaboration, and its work demonstrates the powerful possibilities of authentic collaboration at a time when partisan rancor and stalemate feel inevitable. It proves we can change the world—collaboratively—without anyone relinquishing their core values….(More)”

Science to the People

Curated on Posted on by Stefaan Verhulst

David Lang on how citizen science bridges the gap between science and society: “It’s hard to find a silver lining in the water crisis in Flint, Michigan. The striking images of jugs of brown water being held high in protest are a symbol of institutional failure on a grand scale. It’s a disaster. But even as questions of accountability and remedy remain unanswered, there is already one lesson we can take away: Citizen science can be used as a powerful tool to build (or rebuild) the public’s trust in science.

Because the other striking image from Flint is this: Citizen-scientists  sampling and testing their own water, from their homes and neighborhoods,and reporting the results as scientific data. Dr. Marc Edwards is the VirginiaTech civil engineering professor who led the investigation into the lead levels in Flint’s water supply, and in a February 2016 interview with TheChronicle of Higher Education, he gave an important answer about the methods his team used to obtain the data: “Normal people really appreciate good science that’s done in their interest. They stepped forward as citizen-scientists to explore what was happening to them and to their community,we provided some funding and the technical and analytical expertise, and they did all the work. I think that work speaks for itself.”

It’s a subtle but important message: The community is rising up and rallying by using science, not by reacting to it. Other scientists trying to highlight important issues and influence public opinion would do well to take note, because there’s a disconnect between what science reports and what the general public chooses to believe. For instance, 97 percent of scientists agree that the world’s climate is warming, likely due to human activities. Yet only 70 percent of Americans believe that global warming is real. Many of the most important issues of our time have the same, growing gap between scientific and societal consensus: genetically modified foods, evolution,vaccines are often widely distrusted or disputed despite strong, positive scientific evidence…..

The good news is that we’re learning. Citizen science — the growing trend of involving non-professional scientists in the process of discovery — is proving to be a supremely effective tool. It now includes far more than birders and backyard astronomers, its first amateur champions. Over the past few years,the discipline has been gaining traction and popularity in academic circles too. Involving groups of amateur volunteers is now a proven strategy for collecting data over large geographic areas or over long periods of time.Online platforms like Zooniverse have shown that even an untrained human eye can spot anomalies in everything from wildebeest migrations to Martiansurfaces. For certain types of research, citizen science just works.

While a long list of peer-reviewed papers now backs up the efficacy of citizen science, and a series of papers has shown its positive impact on students’ view of science, we’re just beginning to understand the impact of that participation on the wider perception of science. Truthfully, for now,most of what we know so far about its public impact is anecdotal, as in the work in Flint, or even on our online platform for explorers, OpenExplorer….It makes sense that citizen science should affect public perception of science.The difference between “here are the results of a study” and “please help

It makes sense that citizen science should affect public perception of science.The difference between “here are the results of a study” and “please help us in the process of discovery” is profound. It’s the difference between a rote learning moment and an immersive experience. And even if not everyone is getting involved, the fact that this is possible and that some members of a community are engaging makes science instantly more relatable. It creates what Tim O’Reilly calls an “architecture of participation.” Citizen scientists create the best interface for convincing the rest of the populace.

A recent article in Nature argued that the DIY biology community was, in fact, ahead of the scientific establishment in terms of proactively thinking about the safety and ethics of rapidly advancing biotechnology tools. They had to be. For those people opening up community labs so that anyone can come and participate, public health issues can’t be pushed aside or dealt with later. After all, they are the public that will be affected….(More)”

How to See Gentrification Coming

Curated on Posted on by Stefaan Verhulst

Nathan Collins at Pacific Standard: “Depending on whom you ask, gentrification is either damaging, not so bad, or maybe even good for the low-income people who live in what we euphemistically call up-and-coming neighborhoods. Either way, it’d be nice for everybody to know which neighborhoods are going to get revitalized/eviscerated next. Now, computer scientists think they’ve found a way to do exactly that: Using Twitter and Foursquare, map the places visited by the most socially diverse crowds. Those, it turns out, are the most likely to gentrify.

Led by University of Cambridge graduate student Desislava Hristova, the researchers began their study by mapping out the social network of 37,722 Londoners who posted Foursquare check-ins via Twitter. Two people were presumed to be friends—connected on the social network—if they followed each other’s Twitter feeds. Next, Hristova and her colleagues built a geographical network of 42,080 restaurants, clubs, shops, apartments, and so on. Quaint though it may seem, the researchers treated two places as neighbors in the geographical network if they were, in fact, physically near each other. The team then linked the social and geographical networks using 549,797 Foursquare check-ins, each of which ties a person in the social network to a place in the geographical one.

Gentrification doesn’t start when outsiders move in; it starts when outsiders come to visit.

Using the network data, the team next constructed several measures of the social diversity of places, each of which helps distinguish between places that bring together friends versus strangers, and to distinguish between spots that attract socially diverse crowds versus a steady group of regulars. Among other things, those measures showed that places in the outer boroughs of London brought together more socially homogenous groups of people—in terms of their Foursquare check-ins, at least—compared with boroughs closer to the core.

But the real question is what social diversity has to do with gentrification. To measure that, the team used the United Kingdom’s Index of Multiple Deprivation, which takes into account income, education, environmental factors such as air quality, and more to quantify the socioeconomic state of affairs in localities across the U.K., including each of London’s 32 boroughs.

The rough pattern, according to the analysis: The most socially diverse places in London were also the most deprived. This is about the opposite of what you’d expect, based on social networks studied in isolation from geography, which indicates that, generally, the people with the most diverse social networks are the most prosperous….(More)”