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

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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

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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)”

Can Data Literacy Protect Us from Misleading Political Ads?

Curated on Posted on by Stefaan Verhulst

Walter Frick at Harvard Business Review: “It’s campaign season in the U.S., and politicians have no compunction about twisting facts and figures, as a quick skim of the fact-checking website Politifact illustrates.

Can data literacy guard against the worst of these offenses? Maybe, according to research.

There is substantial evidence that numeracy can aid critical thinking, and some reason to think it can help in the political realm, within limits. But there is also evidence that numbers can mislead even data-savvy people when it’s in service of those people’s politics.

In a study published at the end of last year, Vittorio Merola of Ohio State University and Matthew Hitt of Louisiana State examined how numeracy might guard against partisan messaging. They showed participants information comparing the costs of probation and prison, and then asked whether participants agreed with the statement, “Probation should be used as an alternative form of punishment, instead of prison, for felons.”

Some of the participants were shown highly relevant numeric information arguing for the benefits of probation: that it costs less and has a better cost-benefit ratio, and that the cost of U.S. prisons has been rising. Another group was shown weaker, less-relevant numeric information. This message didn’t contain anything about the costs or benefits of parole, and instead compared prison costs to transportation spending, with no mention of why these might be at all related. The experiment also varied whether the information was supposedly from a study commissioned by Democrats or Republicans.

The researchers scored participants’ numeracy by asking questions like, “The chance of getting a viral infection is 0.0005. Out of 10,000 people, about how
many of them are expected to get infected?”

For participants who scored low in numeracy, their support depended more on the political party making the argument than on the strength of the data. When the information came from those participants’ own party, they were more likely to agree with it, no matter whether it was weak or strong.

By contrast, participants who scored higher in numeracy were persuaded by the stronger numeric information, even when it came from the other party. The results held up even after accounting for participants’ education, among other variables….

In 2013, Dan Kahan of Yale and several colleagues conducted a study in which they asked participants to draw conclusions from data. In one group, the data was about a treatment for skin rashes, a nonpolitical topic. Another group was asked to evaluate data on gun control, comparing crime rates for cities that have banned concealed weapons to cities that haven’t.

Additionally, in the skin rash group some participants were shown data indicating that the use of skin cream correlated with rashes getting better, while some were shown the opposite. Similarly, some in the gun control group were shown less crime in cities that have banned concealed weapons, while some were shown the reverse…. They found that highly numerate people did better than less-numerate ones in drawing the correct inference in the skin rash case. But comfort with numbers didn’t seem to help when it came to gun control. In fact, highly numerate participants were more polarized over the gun control data than less-numerate ones. The reason seemed to be that the numerate participants used their skill with data selectively, employing it only when doing so helped them reach a conclusion that fit with their political ideology.

Two other lines of research are relevant here.

First, work by Philip Tetlock and Barbara Mellers of the University of Pennsylvania suggests that numerate people tend to make better forecasts, including about geopolitical events. They’ve also documented that even very basic training in probabilistic thinking can improve one’s forecasting accuracy. And this approach works best, Tetlock argues, when it’s part of a whole style of thinking that emphasizes multiple points of view.

Second, two papers, one from the University of Texas at Austin and one from Princeton, found that partisan bias can be diminished with incentives: People are more likely to report factually correct beliefs about the economy when money is on the line…..(More)”

Social app for refugees and locals translates in real-time

Curated on Posted on by Stefaan Verhulst

Springwise: “Europe is in the middle of a major refugee crisis, with more than one million migrants arriving in 2015 alone. Now, developers in Stockholm are coming up with new ways for arrivals to integrate into their new homes.

Welcome! is an app based in Sweden, a country that has operated a broadly open policy to immigration in recent years. The developers say the app aims to break down social and language barriers between Swedes and refugees. Welcome! is translated into Arabic, Persian, Swedish and English, and it enables users to create, host and join activities, as well as ask questions of locals, chat with new contacts, and browse events that are nearby.

The idea is to solve one of the major difficulties for immigrants arriving in Europe by encouraging the new arrivals and locals to interact and connect, helping the refugees to settle in. The app offers real-time auto-translation through its four languages, and can be downloaded for iOS and Android….We have already seen an initiative in Finland helping to set up startups with refugees…(More)“

Technology for Transparency: Cases from Sub-Saharan Africa

Curated on Posted on by Stefaan Verhulst

 at Havard Political Review: “Over the last decade, Africa has experienced previously unseen levels of economic growth and market vibrancy. Developing countries can only achieve equitable growth and reduce poverty rates, however, if they are able to make the most of their available resources. To do this, they must maximize the impact of aid from donor governments and NGOs and ensure that domestic markets continue to diversify, add jobs, and generate tax revenues. Yet, in most developing countries, there is a dearth of information available about industry profits, government spending, and policy outcomes that prevents efficient action.

ONE, an international advocacy organization, has estimated that $68.6 billion was lost in sub-Saharan Africa in 2012 due to a lack of transparency in government budgeting….

The Importance of Technology

Increased visibility of problems exerts pressure on politicians and other public sector actors to adjust their actions. This process is known as social monitoring, and it relies on citizens or public agencies using digital tools, such as mobile phones, Facebook, and other social media sites to spot public problems. In sub-Saharan Africa, however, traditional media companies and governments have not shown consistency in reporting on transparency issues.

New technologies offer a solution to this problem. Philip Thigo, the creator of an online and SMS platform that monitors government spending, said in an interview with Technology for Transparency, “All we are trying to do is enhance the work that [governments] do. We thought that if we could create a clear channel where communities could actually access data, then the work of government would be easier.” Networked citizen media platforms that rely on the volunteer contributions of citizens have become increasingly popular. Given that in most African countries less than 10 percent of the population has Internet access, mobile-device-based programs have proven the logical solution. About 30 percent of the population continent-wide has access to cell phones.

Lova Rakotomalala, a co-founder of an NGO in Madagascar that promotes online exposure of social grassroots projects, told the HPR, “most Malagasies will have a mobile phone and an FM radio because it helps them in their daily lives.” Rakotomalala works to provide workshops and IT training to people in regions of Madagascar where Internet access has been recently introduced. According to him, “the amount of data that we can collect from social monitoring and transparency projects will only grow in the near future. There is much room for improvement.”

Kenyan Budget Tracking Tool

The Kenyan Budget Tracking Tool is a prominent example of how social media technology can help obviate traditional transparency issues. Despite increased development assistance and foreign aid, the number of Kenyans classified as poor grew from 29 percent in the 1970s to almost 60 percent in 2000. Noticing this trend, Philip Thigo created an online and SMS platform called the Kenyan Budget Tracking Tool. The platform specifically focuses on the Constituencies Development Fund, through which members of the Kenyan parliament are able to allocate resources towards various projects, such as physical infrastructure, government offices, or new schools.

This social monitoring technology has exposed real government abuses. …

Another mobile tool, Question Box, allows Ugandans to call or message operators who have access to a database full of information on health, agriculture, and education.

But tools like Medic Mobile and the Kenyan Budget Tracking Tool are only the first steps in solving the problems that plague corrupt governments and underdeveloped communities. Improved access to information is no substitute for good leadership. However, as Rakotomalala argued, it is an important stepping-stone. “While legally binding actions are the hammer to the nail, you need to put the proverbial nail in the right place first. That nail is transparency.”…(More)

Website Seeks to Make Government Data Easier to Sift Through

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Steve Lohr at the New York Times: “For years, the federal government, states and some cities have enthusiastically made vast troves of data open to the public. Acres of paper records on demographics, public health, traffic patterns, energy consumption, family incomes and many other topics have been digitized and posted on the web.

This abundance of data can be a gold mine for discovery and insights, but finding the nuggets can be arduous, requiring special skills.

A project coming out of the M.I.T. Media Lab on Monday seeks to ease that challenge and to make the value of government data available to a wider audience. The project, called Data USA, bills itself as “the most comprehensive visualization of U.S. public data.” It is free, and its software code is open source, meaning that developers can build custom applications by adding other data.

Cesar A. Hidalgo, an assistant professor of media arts and sciences at the M.I.T. Media Lab who led the development of Data USA, said the website was devised to “transform data into stories.” Those stories are typically presented as graphics, charts and written summaries….Type “New York” into the Data USA search box, and a drop-down menu presents choices — the city, the metropolitan area, the state and other options. Select the city, and the page displays an aerial shot of Manhattan with three basic statistics: population (8.49 million), median household income ($52,996) and median age (35.8).

Lower on the page are six icons for related subject categories, including economy, demographics and education. If you click on demographics, one of the so-called data stories appears, based largely on data from the American Community Survey of the United States Census Bureau.

Using colorful graphics and short sentences, it shows the median age of foreign-born residents of New York (44.7) and of residents born in the United States (28.6); the most common countries of origin for immigrants (the Dominican Republic, China and Mexico); and the percentage of residents who are American citizens (82.8 percent, compared with a national average of 93 percent).

Data USA features a selection of data results on its home page. They include the gender wage gap in Connecticut; the racial breakdown of poverty in Flint, Mich.; the wages of physicians and surgeons across the United States; and the institutions that award the most computer science degrees….(More)

Accountable machines: bureaucratic cybernetics?

Curated on Posted on by Stefaan Verhulst

Alison Powell at LSE Media Policy Project Blog: “Algorithms are everywhere, or so we are told, and the black boxes of algorithmic decision-making make oversight of processes that regulators and activists argue ought to be transparent more difficult than in the past. But when, and where, and which machines do we wish to make accountable, and for what purpose? In this post I discuss how algorithms discussed by scholars are most commonly those at work on media platforms whose main products are the social networks and attention of individuals. Algorithms, in this case, construct individual identities through patterns of behaviour, and provide the opportunity for finely targeted products and services. While there are serious concerns about, for instance, price discrimination, algorithmic systems for communicating and consuming are, in my view, less inherently problematic than processes that impact on our collective participation and belonging as citizenship. In this second sphere, algorithmic processes – especially machine learning – combine with processes of governance that focus on individual identity performance to profoundly transform how citizenship is understood and undertaken.

Communicating and consuming

In the communications sphere, algorithms are what makes it possible to make money from the web for example through advertising brokerage platforms that help companies bid for ads on major newspaper websites. IP address monitoring, which tracks clicks and web activity, creates detailed consumer profiles and transform the everyday experience of communication into a constantly-updated production of consumer information. This process of personal profiling is at the heart of many of the concerns about algorithmic accountability. The consequence of perpetual production of data by individuals and the increasing capacity to analyse it even when it doesn’t appear to relate has certainly revolutionalised advertising by allowing more precise targeting, but what has it done for areas of public interest?

John Cheney-Lippold identifies how the categories of identity are now developed algorithmically, since a category like gender is not based on self-discloure, but instead on patterns of behaviour that fit with expectations set by previous alignment to a norm. In assessing ‘algorithmic identities’, he notes that these produce identity profiles which are narrower and more behaviour-based than the identities that we perform. This is a result of the fact that many of the systems that inspired the design of algorithmic systems were based on using behaviour and other markers to optimise consumption. Algorithmic identity construction has spread from the world of marketing to the broader world of citizenship – as evidenced by the Citizen Ex experiment shown at the Web We Want Festival in 2015.

Individual consumer-citizens

What’s really at stake is that the expansion of algorithmic assessment of commercially derived big data has extended the frame of the individual consumer into all kinds of other areas of experience. In a supposed ‘age of austerity’ when governments believe it’s important to cut costs, this connects with the view of citizens as primarily consumers of services, and furthermore, with the idea that a citizen is an individual subject whose relation to a state can be disintermediated given enough technology. So, with sensors on your garbage bins you don’t need to even remember to take them out. With pothole reporting platforms like FixMyStreet, a city government can be responsive to an aggregate of individual reports. But what aspects of our citizenship are collective? When, in the algorithmic state, can we expect to be together?

Put another way, is there any algorithmic process to value the long term education, inclusion, and sustenance of a whole community for example through library services?…

Seeing algorithms – machine learning in particular – as supporting decision-making for broad collective benefit rather than as part of ever more specific individual targeting and segmentation might make them more accountable. But more importantly, this would help algorithms support society – not just individual consumers….(More)”

Big data, meet behavioral science

Curated on Posted on by Stefaan Verhulst

Ben Castleman at Brookings: “America’s community colleges offer the promise of a more affordable pathway to a bachelor’s degree. Students can pay substantially less for the first two years of college, transfer to a four-year college or university, and still earn their diploma in the same amount of time. At least in theory. Most community college students—80 percent of them—enter with the intention to transfer, but only 20 percent actually do so within five years of entering college. This divide represents a classic case of what behavioralists call an intention-action gap.

Why would so many students who enter community colleges intending to transfer fail to actually do so? Put yourself in the shoes of a 20-something community college student. You’ve worked hard for the past couple years, earning credits and paying a lot less in tuition than you would have if you had enrolled immediately in a four-year college or university. But now you want to transfer, so that you can complete your bachelor’s degree. How do you figure out where to go? Ideally you’d probably like to find a college that would take most of your credits, where you’re likely to graduate from, and where the degree is going to count for something in the labor market. A college advisor could probably help you figure this out,but at many community colleges there are at least 1,000 other students assigned to your advisor, so you might have a hard time getting a quality meeting.  Some states have articulation agreements between two- and four-year institutions that guarantee admission for students who complete certain course sequences and perform at a high enough level. But these agreements are often dense and inaccessible.

The combination of big data and behavioral insights has the potential to help students navigate these complex decisions and successfully follow through on their intentions. Big data analytic techniques allow us to identify concrete transfer pathways where students are positioned to succeed; behavioral insights ensure we communicate these options in a way that maximizes students’ engagement and responsiveness…..A growing body of innovative research has demonstrated that, by applying behavioral science insights to the way we communicate with students and families about the opportunities and resources available to them, we can help people navigate these complex decisions and experience better outcomes as a result. A combination of simplified information, reminders, and access to assistance have improved achievement and attainment up and down the education pipeline, nudging parents to practice early-literacy activities with their kids or check in with their high schoolers about missed assignments, andencouraging students to renew their financial aid for college….

These types of big data techniques are already being used in some education sectors. For instance, a growing number of colleges use predictive analytics to identify struggling students who need additional assistance, so faculty and administrators can intervene before the student drops out. But frequently there is insufficient attention, once the results of these predictive analyses are in hand, about how to communicate the information in a way that is likely to lead to behavior change among students or educators. And much of the predictive analytics work has been on the side of plugging leaks in the pipeline (e.g. preventing drop-outs from higher education), rather than on the side of proactively sending students and families personalized information about educational and career pathways where they are likely to flourish…(More)”