Oxfordshire County Council has joined forces with Waze, the free crowdsourced traffic and navigation app, in a data-sharing link-up that could help you get from A to B more easily.
Waze is effectively a Sat Nav app you use exactly as you would any in-car navigation device – except Waze has the added benefit of crowd-sourced traffic flow info and county council roadworks as part of the mix. This means that the app can see the traffic hotspots on the roads and route you round them where appropriate, saving you time.
You can use Waze safely and effectively as a standard Sat Nav while taking advantage of the extra information. You can send your own information to help enhance the journeys of others – this must be done either by a passenger or the driver while safe and legal to do so.
It is hoped that with the further development of voice control in the near future Waze will become even easier to use.
The #StartedinOxford Demo Fair is an all-new event, jointly organised by the leading lights of Oxford’s startup community, to celebrate the Oxford startup scene and showcase the best early stage startups Oxford has to offer.
Come along to the event and choose your favourite startup by “investing” in them (each attendee will be given $1,000 #StartedinOxford Dollars) to invest with); the startup with the most investment at the end of the evening will receive a prize!
If you want to get plugged into the startup community in Oxford, then the #StartedinOxford Demo Fair is the place to be!
Our fabulous hosts at TAP Social will be also providing a cash bar, and there will be a variety of nibbles and food on offer to purchase on site.
Outcomes of the many schemes financed by the government to address digital inequalities are rarely uniformly positive or transformative for the people involved.
Numerous academic studies have highlighted the significant differences in the ways that young people access, use and engage with the Internet and the implications it has in their lives. While the majority of young people have some form of access to the Internet, for some their connections are sporadic, dependent on credit on their phones, an available library, or Wi-Fi open to the public. Qualitative data in a variety of countries has shown such limited forms of access can create difficulties for these young people as an Internet connection becomes essential for socialising, accessing public services, saving money, and learning at school.
While the UK government has financed technological infrastructure and invested in schemes to address digital inequalities, the outcomes of these schemes are rarely uniformly positive or transformative for the people involved. This gap between expectation and reality demands theoretical attention; with more attention placed on the cultural, political and economic contexts of the digitally excluded, and the various attempts to “include” them.
Focusing on a two-year digital inclusion scheme for 30 teenagers and their families initiated by a local council in England, a qualitative study by Huw C. Davies, Rebecca Eynon, and Sarah Wilkin analyses why, despite the good intentions of the scheme’s stakeholders, it fell short of its ambitions. It also explains how the neoliberalist systems of governance that are increasingly shaping the cultures and behaviours of Internet service providers and schools — that incentivise action that is counterproductive to addressing digital inequality and practices — cannot solve the problems they create.
We caught up with the authors to discuss the study’s findings:
Ed.: It was estimated that around 10% of 13 year olds in the study area lacked dependable access to the Internet, and had no laptop or PC at home. How does this impact educational outcomes?
Huw: It’s impossible to disaggregate technology from everything else that can affect a young person’s progress through school. However, one school in our study had transferred all its homework and assessments online while the other schools were progressing to this model. The students we worked with said doing research for homework is synonymous with using Google or Wikipedia, and it’s the norm to send homework and coursework to teachers by email, upload it to Virtual Learning Environments, or print it out at home. Therefore students who don’t have access to the Internet have to spend time and effort finding work-arounds such as using public libraries. Lack of access also excludes such students from casual learning from resources online or pursuing their own interests in their own time.
Ed.: The digital inclusion scheme was designed as a collaboration between a local council in England (who provided Internet services) and schools (who managed the scheme) in order to test the effect of providing home Internet access on educational outcomes in the area. What was your own involvement, as researchers?
Huw: Initially, we were the project’s expert consultants: we were there to offer advice, guidance and training to teachers and assess the project’s efficacy on its conclusion. However, as it progressed we took on the responsibility of providing skills training to the scheme’s students and technical support to their families. When it came to assessing the scheme, by interviewing young people and their families at their homes, we were therefore able to draw on our working knowledge of each family’s circumstances.
Ed.: What was the outcome of the digital inclusion project —- i.e. was it “successful”?
Huw: As we discuss in the article, defining success in these kinds of schemes is difficult. Subconsciously many people involved in these kinds of schemes expect technology to be transformative for the young people involved yet in reality the changes you see are more nuanced and subtle. Some of the scheme’s young people found apprenticeships or college courses, taught themselves new skills, used social networks for the first time and spoke to friends and relatives abroad by video for free. These success stories definitely made the scheme worthwhile. However, despite the significant good will of the schools, local council, and the families to make the scheme a success there were also frustrations and problems. In the article we talk about these problems and argue that the challenges the scheme encountered are not just practical issues to be resolved, but are systemic issues that need to be explicitly recognised in future schemes of this kind.
Ed.: And in the article you use neoliberalism as a frame to discuss these issues..?
Huw: Yes. But we recognise in the article that this is a concept that needs to be used with care. It’s often used pejoratively and/or imprecisely. We have taken it to mean a set of guiding principles that are intended to produce a better quality of services through competition, targets, results, incentives and penalties. The logic of these principles, we argue, influences they way organisations treat individual users of their services.
For example, for Internet Service Providers (ISPs) the logic of neoliberalism is to subcontract out the constituent parts of an overall service provision to create mini internal markets that (in theory) promote efficiency through competition. Yet this logic only really works if everyone comes to the market with similar resources and abilities to make choices. If their customers are well informed and wealthy enough to remind companies that they can take their business elsewhere these companies will have a strong incentive to improve their services and reduce their costs. If customers are disempowered by lack of choice the logic of neoliberalism tends to marginalise or ignore their needs. These were low-income families with little or no experience of exercising consumer choice and rights. For them therefore these mini markets didn’t work.
In the schools we worked with the logic of neoliberalism meant staff and students felt under pressure to meet certain targets — they all had to priortise things that were measured and measurable. Failure to meet these targets would then mean they would have to account for what went wrong, face losing out on a reward or they would expect disciplinary action. It therefore becomes much more difficult for schools to devote time and energy to schemes such as this.
Ed.: Were there any obvious lessons that might lead to a better outcome if the scheme were to be repeated: or are the (social, economic, political) problems just too intractable, and therefore too difficult and expensive to sort out?
Huw: Many of the families told us that access to the Internet was becoming evermore vital. This was not just for homework but also for access to public and health services (that are being increasingly delivered online) and getting to the best deals online for consumer services. They often told us therefore that they would do whatever it took to keep their connection after the two-year scheme ended. This often meant paying for broadband out of their social security benefits or income that was too low to be taxable: income that could otherwise have been spent on, for example, food and clothing. Given its necessity, we should have a national conversation about providing this service to low income families for free.
Ed.: Some of the families included in the study could be considered “hard to reach”. What were your experiences of working with them?
Huw: There are many practical and ethical issues to address before these sorts of schemes can begin. These families often face multiple intersecting problems that involve many agencies (who don’t necessarily communicate with each other) intervening in their lives. For example, some of the scheme’s families were dealing with mental illness, disability, poor housing, and debt all at the same time. It is important that such schemes are set up with an awareness of this complexity. We are very grateful to the families that took part in the scheme and the insights they gave us for how such schemes should run in the future.
Ed.: Finally, how do your findings inform all the studies showing that “digital inclusion schemes are rarely uniformly positive or transformative for the people involved”. Are these studies gradually leading to improved knowledge (and better policy intervention), or simply showing the extent of the problem without necessarily offering “solutions”?
Huw: We have tried to put this scheme into a broader context to show such policy interventions have to be much more ambitious, intelligent, and holistic. We never assumed digital inequality is an isolated problem that can be fixed with a free broadband connection, but when people are unable to afford the Internet it is an indication of other forms of disadvantage that, in a sympathetic and coordinated way, have to be addressed simultaneously. Hopefully, we have contributed to the growing awareness that such attempts to ameliorate the symptoms may offer some relief but should never be considered a cure in itself.
Oxford Mathematician Neave O’Clery recently moved to Oxford from the Center for International Development at Harvard University where she worked on the development of mathematical models to describe the processes behind industrial diversification and economic growth. Here she discusses how network science can help us understand the success of cities, and provide practical tools for policy-makers.
Urban centres draw a diverse range of people, attracted by opportunity, amenities, and the energy of crowds. Yet, while benefiting from density and proximity of people, cities also suffer from issues surrounding crime, transport, housing, and education. Fuelled by rapid urbanisation and pressing policy concerns, an unparalleled inter-disciplinary research agenda has emerged that spans the humanities, social and physical sciences. From a quantitative perspective, this agenda embraces the new wave of data emerging from both the private and public sector, and its promise to deliver new insights and transformative detail on how society functions today. The novel application of tools from mathematics, combined with high resolution data, to study social, economic and physical systems transcends traditional domain boundaries and provides opportunities for a uniquely multi-disciplinary and high impact research agenda.
One particular strand of research concerns the fundamental question: how do cities move into new economic activities, providing opportunities for citizens and generating inclusive growth? Cities are naturally constrained by their current resources, and the proximity of their current capabilities to new opportunities. This simple fact gives rise to a notion of path dependence: cities move into new activities that are similar to what they currently produce. In order to describe the similarities between industries, we construct a network model where nodes represent industries and edges represent capability overlap. The capability overlap for industry pairs may be empirically estimated by counting worker transitions between industries. Intuitively, if many workers switch jobs between a pair of industries, then it is likely that these industries share a high degree of knowhow.
This network can be seen as modelling the opportunity landscape of cities: where a particular city is located in this network (i.e., its industries) will determine its future diversification potential. In other words, a city has the skills and knowhow to move into neighbouring nodes. A city located in a central well-connected region has many options, but one with only few peripheral industries has limited opportunities.
Such models aid policy-makers, planners and investors by providing detailed predictions of what types of new activities are likely to be successful in a particular place – information that typically cannot be gleaned from standard economic models. Metrics derived from such networks are informative about a range of associated questions concerning the overall growth of formal employment and the optimal size of urban commuting zones.
You can explore diversification opportunities for cities and states in Colombia using network mapping tools (as shown in the figure below) by visiting www.datlascolombia.com.
This research was conducted by Neave and colleagues primarily at the Center for International Development at Harvard University, in collaboration with Prof. Ricardo Hausmann, Eduardo Lora and Dr Andres Gomez. To see the working papers click the links:
Figure caption (click on it to enlarge): a network of labour flows between industries for Colombia. Nodes represent industries, and are colored by sector. It is observed that closely related industries tend to cluster, driven by workers transitioning between similar economic activities. This network models the flow of know-how within the Colombian economy, and can be used to model the path dependent process of industrial diversification for urban centres.