This past week our team of researchers and trained interviewers were dispatched to collect the first round of data. Through interviews and quantitative surveys, a number of issues are easily observed. Interviews are used to understand what might be difficult to measure and tabulate. So, we design questions that stimulate the person we’re interviewing (we cal them respondents) that encourage layers of responses. The skill here is in listening to the respondent without bias. That means listening without trying to add one’s own personal opinion about what they are saying. Instead, we try to encourage respondents to say more, and explore the various themes we’re tasked to interview them about. You could look at Gail Jennings’ study about public transport in Africa. Here we can see that tabulating responses helps to at least synthesize information captured like this; but we also see significant limits in the response rates of these experts.
Quantitative questionnaires try to capture what we can measure. Things like age, level of education, preferred mode of transport and all that. These are things that respondents can clearly indicate to us what their response is. On the other hand, you could ask them to rate, rank, compare, choose and many others. Some of these require statistical techniques to develop the survey; others only need to be consistent with theoretical principles and then analysis can take place through mathematics, statistical and econometric techniques. Why’s this bit of theory important?
For starters, it takes me some time to actually develop papers that I am keen to publish. Largely because data collection is a complex skill which requires time and practice. Some researchers approach it as the reviewer’s responsibility; but for me, it’s a skill that requires practice, consultation and experimentation— then reporting on the broad array of findings. Some call it slow scholarship, I call it patient research. So that even without large volumes of publication units, the underlying research activities lead up to the broader set of results we report on is a culmination of so much raw ore.
In this sense evidence is derived from ‘praxis’. That is, action based research; practical research which contributes to building communities that work, execute, administer and therefore implement. Policy research reveals that policy implementation is deeply tied to administration. Administrative skills involve developing the paper work, the performance incentives for teams, and the measurement tools to evaluate progress. So here’s the thing: people, problems and institutions evolve all the time. The data collection snapshot takes only one picture at a specific point in time—call this a cross-sectional study. We cut through a specific section of time associated with this policy problem. Or if we observe the problem over time, interviewing the same people over and over again, every year— then we could call the study longitudinal. How much truth is in collecting data? Does the public really value it?
“The notion of translational urban research praxis captures more than the idea of applied research, or even co-production, and encompasses integrating the research conception, design, execution, application and reflection– and conceiving of this set of activities as a singular research/practice process.”
Susan Parnell & Edgar Pieterse (2015) ‘Translational global praxis: Rethinking methods and modes of African urban research”. International Journal of Urban and Regional Research.
Lessons from surveys so far
One lesson from this year’s surveys so far, is that some people do not see the importance of having their voices heard. One group of commuters said to our team that “we’re not interested, because it’s all useless”; an older man stood with me for about 40 minutes explaining the political system. He has a wealth of insights about show the transport industry evolved in his province. When I asked what value surveys add, and if he’s ever been interviewed, he said: “bring me to your meetings; these surveys mean nothing to me!”
There’s also another group of people who feel that surveys are valuable and interesting. Valuable in a sense that knowing what the public believes in and looks forward to enables better policy decisions. One commuter said “I find the survey interesting, and if they implement your recommendations, things should improve”. Another said: “the survey made me think about things I don’t always think about”. In my previous work, experimenting with surveys made me realize that some surveys actually teach people what they think about specific issues. One study experiment with university students taught me that surveys with ratings and games can become self-exploratory and valuable. What I don’t know of is how long the effects of this self knowledge last.
Then comes the experiential side of research, which is quite easily neglected. That is: if a person experiences a certain service or situation how will the impression the experience makes affect their rationalization and thinking about the world around them. The world within, and the exterior: do they change habits, social norms, or other aspects of their lives? Mac Mashiri for example has been part of studies which involve following learners and documenting their journeys to school. Unlike a documentary or videographic representation, they report and narrate each journey. Or take a turn to Transport Truths, which practically may serve as an archive of insights about commuter needs in audio, visual and empirical formats. There’s significant room to integrate information systems, artificial intelligence and media to this format of experiential research. Then we have studies which the likes of Tommy Gärling and others get involved in that attach emotions to travel experiences in a way that purports that through experience new habits are formed. At least a new option of behavior is added to the decisions people make.
One could also take the experiential model one step further by actually inducing activities and environments which encourage deeper exchange and behavioral reforms. Consider the OpenStreets Cape Town movement, which habitually closes of streets to encourage people to get wild and in the funnies about their streets. This model can have transformative effects on residents, especially those who seldom have the kind of security and safety one expects from a street. Or Rory Williams’ efforts around the #biketowork personal campaign, which gets him and others to travel to work each day by non-motorized transport.
A new era of transport policy
Perhaps we’re entering a new era of transport policy making. One where policies do not emerge as a result of sudden changes in the market, but may come from deeper forms of data collection. As much as ‘big data’ n=all implies significant analytical power, there’s still a missing conversation– literally. In this sense, there may be some room to explore new questions, set new policy agendas, and philosophical positions which explore the meanings of fair, just, value, equal, equitable and so on– beyond the legal labyrinth. Here I’m reminded about Alfred Khan’s long footnote about fairness in economic regulation in which he simply highlights how complex of a topic “fair” allocation in economic terms truly means. As technology progresses, human capacity for understanding and navigating through social systems needs to complement the advancements. At the end of the day, we need solutions which are not only technically sound; but interventions that resonate with the heart of our people today and tomorrow without fail.
If you’ve been collecting data, or surveying people: share your thoughts about the impressions this experience has left on you. I’m quite keen to open this can of worms. Thank you for reading up and have a wonderful week.
Hlulani 