Can You Stay? examines one discrete variable among many complex and converging issues concerning housing precarity, focusing on a part of the world with unique geography and social issues.
Project Background
This map is cut from the cloth of a capstone project I did in 2018 at the Centre for Geographic Sciences (Lawrencetown, Nova Scotia, Canada), where students were required to develop a mapping solution for a third party.
A family friend worked as the director of the local women’s centre, and I asked them whether maps would be of any service to their work. As it turned out, they already had an idea in mind — the women’s centre had been collaborating with local housing coalitions and public health officials to produce a series of reports on housing precarity in southwestern Nova Scotia, a rural part of Canada’s east coast. These reports illuminated the reality that many working people are at risk of homelessness and examined why this is so in this part of the world. They’d been thinking for some time of employing maps to visualize the data and provide a compelling complement to their reporting.
Exploring the Data
The concept of housing as a social determinant of health was a relatively new idea to me. I imagine that in this pre-pandemic ‘Before Time,’ public health in general was probably a novel topic for many people.
Much of the report data came from a survey the participating groups had conducted, (http://www.daashgroup.com) asking respondents a variety of questions related to housing needs.
The voices of rural Nova Scotians express concerns of a tenor different from those of the precariously housed/homeless in cities or in other parts of the world. The survey was able to capture and quantify some aspects of this reality.
For example, let’s say it’s more common for a working-class person to own a home in Atlantic Canada than in Southern Ontario. It’s tempting to think a homeowner in Shelburne County is unquestionably better off than an apartment-dweller in the Greater Toronto Area. But what if:
· They can’t get the firewood to heat this building they own?
· The person lives a 60-mile commute from where the jobs are, and can’t afford car repairs this month?
· Internet is murderously slow in their community, so they aren’t able to work from home?
Or maybe a Nova Scotian is unhoused, and while not sleeping rough on the street, visible to passers-by as might be the case in an urban area, they’re ‘invisibly homeless,’ perhaps finding temporary places to sleep on friends’ couches, tents on the outskirts of town, or a hunt-camp in the woods. This person’s needs might be quite different from those unhoused in a city.
Although the survey was anonymous and confidential, responses were linked to broad geographical areas within the study area, giving cartography and spatial analysis relevance to the project.
To satisfy my academic requirements, I created a series of posters and graphs to support this reporting. I presented my findings at a housing symposium held in 2019, which was attended by housing coalition members and decision-makers. Work done by these groups has helped to identify needs within our communities and inform new initiatives to help residents. (http://www.tricountywomenscentre.org/vibrant-homes.html)
Guerrilla Cartography Map-Making Process
When I first heard about Shelter: An Atlas, I was excited by the idea that, with a little reworking, my topic could perfectly dovetail into the project. I’m pretty sure I pulled together the initial draft of the map within one day of hearing about the atlas!
There were so many dimensions to the data collected. To narrow it down to one graphic for inclusion in the atlas, I chose a survey question that, while a simple yes/no question, struck me as weirdly trenchant: "Are you able to stay where you're currently living?"
I enjoy drawing by hand, but this is usually limited to little doodles during protracted Zoom meetings. At the time of pulling together this submission, I’d just gotten an iPad and wanted to experiment merging vector map graphics with digital sketching and painting, to create work that was technically precise but looked imperfect and hand-drawn. To accomplish this, I used QGIS 3 and Statistics Canada shapefiles to design the mapping, exported each layer to an image file, then redrew them in the Procreate iPadOS app. I recombined them and added a few additional effects using Photoshop.
In reviewing the housing survey results, the most compelling thing to me wasn't the statistics that could be gleaned from them (which I massaged, parsed, and merged with Canadian census data using Python to create more comprehensive reporting not included in this piece), but the narrative comments offered up by participants.
Southwestern Nova Scotia’s communities are relatively sparse in population, and although the survey received enough responses to render it suitable for statistical analysis within broadly delineated geographical areas, the dataset was still small enough that individual responses stood out as unique voices in ways that just weren’t eligible for use in data science or as cartographic visual variables.
In the science-based reporting style I’ve been trained in, we're encouraged to disregard subjective data and anecdote. However, I think this sort of qualitative data can greatly enhance reporting, especially with respect to social issues. Individuals who are experiencing first-hand the issues of study can advance our knowledge with more credibility and authority than those whose understanding is theoretical. So I was enthusiastic about including the text of some of these comments in the mapping.
People can understand these situations more readily when hearing the first-person perspective, connecting the data to personal storytelling. The hand-lettered quotes on my map from survey participants, in addition to matching the unfastidious aesthetic I chose, are intended to make viewers aware that they’re reading comments written by actual people.
About the Cartographer
I do GIS analysis and database work at my day job, but I value the use of cartography untethered from strictly commercial applications as a form of expression and a source of transformative knowledge-sharing. So I also make a point of using my skills for solving spatial problems in support of environmental or humanitarian work, by creating fine art maps to support grassroots fundraising initiatives, and always following mercurial paths of creativity to see what comes of it. Despite having zero university degrees, I try to keep an eternal student’s frame of mind, and I’m currently experimenting with graph databases, natural language processing, and digital painting.