Information Literacy, Census Geography, and Maps

One of the things I’m constantly doing as a government documents librarian is giving lessons on Statistics Canada geographic areas. Census geographies can be downright confusing to the new user (and to sometimes to the seasoned expert!). The names are riddled with acronyms and jargon, and their relationships to other areas and spaces can be complicated. One legally incorporated township may be considered a census subdivision while another may be classified as only a census agglomeration. Another city may be classified as a census subdivision, and also be part of a census metropolitan area of a similar name, e.g., Toronto CSD and Toronto CMA.   Or, a city may be classified as a census subdivision and exist not only in a CMA with a similar name, but also a census division (I’m looking at you, City of Waterloo CSD, Waterloo Region CD, and Kitchener-Cambridge-Waterloo CMA). And if you dare introduce census tracts the first time through, your short introduction to the “Russian dolls” nature of census geographies runs the risk of turning your lesson into an information dump about privacy and data validity when all that your first-year economics student wanted to know was why it’s so hard to get comparable income and migration numbers for Kitchener, Ontario, and The Pas in northern Manitoba.

Don’t ask me how many census tracts this CMA holds.

Confusion abounds. One of the problems we encounter are the tools we use to explain these geographies, which should be easily understood but are often abstract – we may live in towns and cities, but we refer to them as census agglomerations or CMAs. What can you use to show how spaces relate to one another, or how certain concepts can be measured and expressed spatially? The answer is a map, of course.  God lov’em, those maps. Maps help us express numbers – quantities, amounts, rations, proportions – with colours and shapes, and in the regions we live in and travel through each day. Face it, “big data” wouldn’t be as big as it is today if we didn’t have “big maps” to help use make sense of the numbers. However, StatCan’s digitized maps are large, layered PDFs that aren’t always user-friendly. The Standard Geographical Classification (SGC) PDFs are great reference items, but they aren’t very accessible.  And this creates a learning gap for so many of our users.

To overcome this gap, I’m constantly pulling out the old SGC print maps, and I’m also cutting and pasting and hacking together magnified screenshots of the PDFs into my slide deck.  Typically, if you need census help and you’ve found me in person, then there stands a good chance that I’m going to crack open the SGC and unfold a map somewhere in the office (I even keep the southern Ontario CD-CSD map posted to a wall).  I started doing this last Spring after I moved to Waterloo and had to learn the region’s geography and confirm its census divisions, subdivisions, and CMAs for myself, and I realized this was a simple and effective tool that should be used more often, especially with new StatCan users.

StatCan’s 2006 geographies for southern Ontario, from a summer 2012 research consultation

 

Typically, I bring students to a nearby conference room and unfold the map on a large table.  I find that being able to “walk around” the entire map and point to the places where the lines that signify the different geographies merge, separate, and then merge again, helps students understand some of the logic behind the regions (at least in terms of distance and population). They may not always be able to recall all the differences between a census division, subdivision and metropolitan area after a session, but they at least remember that there are differences, and these differences are important enough to affect their research.

The original SGC PDF gives us a wide view of Ontario

The classroom is a different story, though. When working with only one person or a small group, there is a persuasive element at work that captures everyone’s attention. Carefully unfolding and presenting a map to a small group of people is like opening a box that holds a surprise. (Let’s call this surprise “knowledge” and we’ll call ourselves awesome for charming our audience so handily into learning something). But if we take that same map into the classroom or lecture hall, it risks becoming an awkward, cumbersome prop. It can become a distraction or even a failed means to demonstrate your expertise in such a short time to such a large group of people.

Zooming in reveals the different geographies

Maps that unfold to become wider and taller than you put the room’s attention onto your map-wrangling skills (however good or poor they might be) instead of on the knowledge you have share, so I avoid them. You’ve never caught me walking to a classroom with a print map, and I doubt many other librarians do that today.

The final zoom focuses directly on the region the classroom is interested in (and it’s often Waterloo Region)

Instead, I give the class what they want and what they expect, and that means I work that map into my PowerPoint deck. Any time I’m introducing StatCan resources and geographies to a class, I insert three images of the same PDF map, each one magnified more than the last. This helps people “zoom in” with their eyes and see the many relationships and regions that are defined in one place alone. The length of time I spend on these slides depends on the classroom’s needs: sometimes, I spend only a few moments on these slides, and other times, I’ll spend five or ten minutes. What matters is that after I’ve finished up and am headed back to the office, I know that the instructor can pass around a slide deck that always refers to all these different areas.

I know I’m not presenting anything new in this post: maps have long been a tremendous tool within government documents librarianship. Perhaps the takeaway lies more in information literacy than it does anywhere else. Is your digital resource, as presented to you, the best way to help the user understand the resource? You may want to turn to the print resource or manipulate the digital resource, as I do with StatCan maps, to improve learning and synthesis. It’s just one more tool (or two, in this case) in our IL toolbox.

Halifax Maps: 2005 Median Income, Married-Couple Families

This week’s map shows us 2005 median incomes for married-couple families in Halifax, Nova Scotia.  Don’t let that long topic get to you: although Statistics Canada can sometimes get a little difficult with their language, it’s not too hard to decipher:

2005 median income – This is not the average income for the tract but the income that separates the top half of reported incomes from the lower half of incomes in the area.  This is a commonly used value when considering income because it prevents incredibly high and incredibly low incomes from affecting a stated average.

married-couple families – StatCan records income for different family types.  There are lone-parent families, of which “female-lone parent” and “male-lone parent” are subsets.  StatCan also lists dual-parent families (my term).  In these are two distinct kinds: married-couple families and common-law families. However, Statistics Canada does not combine these values for us into one field as they do with lone-parent families, so we must consider them individually.

2010_0525_median_income_married

[Click here for a full-window map.]

Two interesting patterns emerge on this map.  The first pattern is the manner in which lower median incomes become prevalent as one moves west to east.  The further into old Halifax County one drives, the lower the median income will be.  Presumably, lower rural-based incomes and dual-parent families who hold only one reported income between them account for this.  Note, however, that in rural western Halifax county, we nonetheless find higher incomes: the incomes over extreme western Halifax are nearly double the incomes in extreme eastern Halifax.

The second pattern is the high incomes to be found on Halifax Peninsula and along the Bedford Basin.  These incomes should be expected, given the socio-economic patterns we see in these areas (e.g.: highly educated, fully employed households). What is of interest, though, is the proximity of Halifax’s highest median income to its lowest:

Highest income for married couples in Halifax:

  • Tract 2050005.00 (which I’ve called South End-Gorsebrook), lying on the peninsula’s shores:  $194,622

Lowest income for married couples in Halifax:

These tracts, nearly side-by-side one another on the Halifax Peninsula, house two distinct populations that are tied at the hip – the student underclass studying and working at the post-secondary schools and hospitals that dot the south end, and the professional class that is employed by these institutions.  I’m painting with broad strokes here, of course, but it does serve as a little bit of context to explain how these two different income levels lie within only two or three kilometres of one another.

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Halifax Marital Status by Census Tract, 2006

Today’s map is a Valentine’s Day treat for all the single ladies and men in Halifax, Nova Scotia.  By manipulating  2006 Census data at the tract level, I’ve plotted maps that show the marital status of all the men and women in Halifax.(*)

1.  Women who are not in a married relationship in Halifax, Nova Scotia, 2006 Census:

Women not in a married relationship in Halifax, 2006 Census

2.  Men who are not in a married relationship in Halifax, Nova Scotia, 2006 Census:

Men not in a married relatonship in Halifax, 2006 Census

(*) Careful attention must be given to meaning of these values.  These maps represent the marital status of all people living in a tract, over the age of 15 – a question that was asked on the 2006 Census.  When a person was asked this question, they could respond by stating that they were:

  • Never legally married (single)
  • Legally married (and not separated)
  • Legally married (but separated)
  • Divorced
  • Widowed

For the purposes of these maps, I have considered anyone who answered “Never legally married (single)”, “Legally married (but separated)”, “Divorced”, or “Widowed” to be your potential special some one who you might meet by accident walking down Spring Garden Road on a sunny, Sunday afternoon.

Note, however, that this census question does not take into account people who are living in a common-law relationship.  StatCan was concerned with marital status as opposed to “relationship status” when asking this question.  The number of common-law relationships in a tract therefore muddles the values because some one who is “never been married (single)” or “divorced,” for instance, may actually be living with some one in a common-law relationship.  In the future I’ll manipulate the numbers to account for this, so for now understand that these maps, strictly speaking, reflect marital status in Halifax, Nova Scotia.

Summary Data:

Population of Halifax, aged 15 or above: 312,650

  • Males, 15+: 148,390
    • Males 15+, not in a marital relationship: 74,490 (50.2%)
  • Females, 15+ 164,260
    • Females, 15+,  not in a marital relationship: 90,350 (55.0%)

Please feel free to comment on the maps or to note any errors to be corrected.  In the mean time, Happy Valentine’s Day.

Citations and disclaimers.

These maps were published with data gathered from Statistics Canada 2006 Census Tracts as well as from aggregated data retrieved from the Equinox data delivery system (Tables 97-552-XCB2006005 and 97-552-XCB2006006).  This data was used strictly for scholarly research purposes and in no way in the pursuit of any commercial or income-generating venture.

Halifax maps – 2006 population per census tract

Given the fact that I am working with data from the 2006 Census Tracts, I decided it would be important to begin by plotting a map that shows the population of Halifax Regional Municipality per census tract (CT).

20100104_2006_HRM_Census_Tracts_Population

What’s important to understand when looking at this map is that these are representations of just whole numbers – we’re not looking at a population rate of decline or density.  StatCan’s census tracts, rather, are developed by a set of guidelines that take in account more than only population rates.  Boundaries should follow easily recognizably physical boundaries or major arteries and have populations between 2500 and 8000 (ideally around 4000); the areas must be as compact as possible; and the populations should ideally be homogeneous in terms of socio-economic conditions (source).  Therefore, CTs with lower populations on Halifax Peninsula are more likely indicative of latent socio-economic factors that promote lower densities that any sort of StatCan motive to consider these tracts as demanding special attention.

My next map, I think, will demonstrate density or growth rates.  There was upwards of an 11% population growth rate in the Clayton Park area between 2001 and 2006, but the area’s surround census tracts didn’t see nearly as large an increase – that might be interesting to demonstrate on a map.

Finally, if there is a lesson to be learned on the production of this map, it’s to avoid using a blue gradient for HRM since it blends so easily with the shoreline and ocean.  My next colours will be bolder, for sure.