Canada dominates the global mining industry. Canadian companies operate in over 100 countries around the world (some sources claim Canadians own seventy-five percent of the world’s extractive companies). Fifty-seven percent of the world’s public mining corporations are listed on the Toronto Stock Exchange. Canadian mining stimulates the market economy, employs hundreds of thousands of global citizens, and disrupts societies and environments on every continent. Although often hidden from our gaze, we directly benefit from its products: minerals and metals hold up the buildings around us, power our vehicles, and conduct electricity in the screen you’re reading this on right now.
My research on the 1909 Porcupine Gold Rush in Northern Ontario shows how the roots of this massive, Canadian-centric international mining industry stretch back at least as far as the beginning of the twentieth century. With a few exceptions, most mining research has been inward looking – historians are interested in questions of how the industry shaped the state over time, and vice versa. My outward-looking research was motivated by the observation that the Canadian experience was not unique (other nations experienced similar histories of gold rushes and industrialization), and, further, that science, money, and corporations crossed permeable national boundaries relatively frequently in the early twentieth century.
But the transnationalism of Canadian mining is not an obvious feature of the documentary evidence. My study area, the Porcupine, certainly experienced a lot of local social and environmental changes – including the appropriation resources from indigenous people, significant land and water-scape modification, and the industrialization of Northern Ontario. Hints of a more international experience crop up sporadically in the archives. For example, a geological report written in Ontario might cite South African studies, or a miner might have come over as a Prisoner of War in 1916, or a mine manager might have written to colleagues in South America looking for labour statistics. But even if you are looking for them, these international connections are difficult to make sense of because they come from a huge diversity of sources and do not have any kind of inherent order.
Historical Geographical Information Software helped turn this uneven and scattered evidence into more comprehensible global story. As I researched in the archives, I kept an active database of “moved things” encountered in the evidence. Having just finished my third chapter, I have a list of around 150 moved people, objects, and ideas for the period (roughly) between 1909 and 1929. These are represented on the map below.
The Porcupine Gold Rush began in 1909 when prospectors and indigenous guides uncovered rich surface deposits under the moss near Porcupine Lake (near the modern town of Timmins). In a context of economic recovery and on the heels of similar discoveries in the Klondike and South Africa, the area was rapidly “staked up” by corporate syndicates (based primarily in the US, Canada, and Europe) and developed into an industrial mine site.
The map shows how, in general, people and ideas moved further and more frequently than objects. There are obvious reasons for this. It was easier and cheaper for people and corporations to bring in physical goods from geographically proximal locations. Equipment, for example, often came from the north-eastern US, timber for headframes came from British Columbia, and groceries for Porcupine came from Southern Ontario.
How did these patterns change over time? To address this question, I moved the same data over to Tableau (ArcMap does not deal with time very well).
In Tableau, I can see how before 1911 (in the staking and financing period) most international influence came from other mining zones (Australia, the West, New Zealand, and South Africa). After 1911, this changed. People, ideas, and objects came from Europe. These patterns suggest the importance of Ontario’s connection to European/neo-European science and society. After 1911, mining had become established at Porcupine and the people, technology, and ideas of other gold frontiers became less practical in Ontario. In other words, the gold rush “bonanza” moment had passed. From 1911 on, the Porcupine’s historical trajectory merged with broader trends in industrial mining around the world driven from intellectual centers in Europe.
During the First World War, mining slowed. The companies hunkered down on their properties and did whatever work they could – mostly exploring, geological work, and improving efficiency. When the markets finally began to pick up again in the 1920s, the mines were ready. Armed with improved understandings of their deposits, efficient machinery, and having avoided physical damage during the war, they were well-placed to take advantage of post-war demands for metals. A massive new program of industrial production began. It was powered primarily by an influx of labour, both from returning miners and from Europeans who had been displaced by conflict between 1914 and 1918. Documentary evidence in the early 1920s (especially the 1921 census) reflects this shift.
Disclaimers & Problems
Like any good humanist, I am aware that this type of analysis has limits. Here are just a few:
- The maps do not represent an exhaustive list of all moved things in the world, or even all the moved things that came to Porcupine. What I have collected is merely a selection. Even if I was to somehow manage to write a list of every moved person, object, and idea in the documentary evidence, I would still be missing a lot: Many moved things were unrecorded, especially if they belonged to marginalized people.
- Things are complicated. I engaged in a considerable amount of simplification in creating my database, and it still proved too complicated for the software. Lots of things (especially ideas and people) came from multiple places. I was unable to represent this kind of complexity on the map. Also, boundaries between categories are inherently messy. For example, many people also brought ideas or objects with them.
- Individual details get lost. As informative as this kind of “big picture” analysis might be, there is something sad about the way it obscures the most interesting part of the past. A host of colourful individuals (Mary Couttes, English restaurateur, Reuban D’Aigle, a Klondike veteran, “Fong Horn,” a Chinese café owner) become just another line pouring into Porcupine alongside hundreds of identical lines.
In the End…
As a whole, the map(s) show the truly global nature of mining much more effectively than a simple human survey of the documentary evidence. This is an example of digital techniques doing something totally beyond my capacity as an individual historian (within a reasonable time frame). The maps pull undercurrents of the primary evidence to the forefront, complicating our understandings of history.
Mining in Canada was shaped by a wide range of people, objects, and ideas. Although dominated by Europe and Neo-European states, influences came from a hugely wide variety of places – India, Syria, China, and North Africa being some of the most surprising. Speaking about mining as a purely local or national phenomenon in Canada ignores the industry’s rich history of interaction with the rest of the world.
For most readers, that’s all you need to know. But for anyone considering a similar project, read on for some “how to.”
Take a Look Under the Hood: How to Make a Flow Map in ArcGIS
Your CSV spreadsheet must have at least 4 columns: Some kind of ID field, start point latitude, start point longitude, end point latitude, and end point longitude (circled below).
I have many additional columns. This is for methodological reasons (ie. source) and sometimes for reasons of ignorance (DO NOT FORMAT THE DATES LIKE I DID. Excel will “helpfully” auto-format them, and its difficult to get them back. If I was to do it again, I would use a dd/mm/yyyy format). Remember that a simple spreadsheet makes for a happy ArcGIS. Extra columns with weird punctuation in them might make the tool fail.
Next, Open up ArcMap and add a base map of your choosing. I used “Imagery” from ArcGIS online. Open ArcToolbox. Go to Data Management Tools -> Features -> XY to Line. Clicking the folder icon next to “input table” will allow you to browse for your spreadsheet. Choose a location for your output. Then tell Arc where to find your start lat and long using the drop-down menu (these will automatically populate from your spreadsheet).
Then, and this is very important, make sure your coordinate system matches your basemap.
Once you click OK, the tool will go to work…and hopefully produce a map with lines on it!
Note: To get the yellow dots at the start and end of my lines (as in the first image in this post), I used File -> add data -> add xy data. I used the same spreadsheet, but used only the origin x/y coordinates. I then repeated the process for the final location coordinates. I created two new shapefiles from the result.
Take a Look Under the Hood: How to Make a Flow Map in Tableau
Annoyingly, Tableau requires your database be oriented totally differently than Arc. The start and end points must be stacked on top of each other, as shown. So for Tableau you need at least 4 columns: a unique identifier for each (here it is “item”), a common identifer for each (in my table, “name”), latitude, and longitude.
re-organising my database required some considerable gymnastics in excel. I won’t go into the detail, but basically I achieved this by copying my end points below my start points, then using my “item” numbers to “sort” the rows so that they ended up on top of each other. Then I deleted enough cells in each row to get the end x points under the start x points. This messed up the rest of my rows considerably, but Tableau cannot really use that information usefully anyway….and I have it in my original database for reference…so I just ignored the chaos and plowed onwards.
Notes: I had to fix my dates in order to see change over time. It was painful. Also, Tableau prefers straight up excel format, so no need to convert to .csv.
Next, open Tableau and connect to your table. Make sure you tell Tableau which columns are your lat and long (below). You may also need to tell it which column is your dates if you’re interested in tracing change over time.
Click Go to Worksheet. Drag X into the columns bar and Y into the Rows Bar. Note: they may show up as (AVG) when you do this. If this is the case, you need to click the drop-down menu next to X and Y and make them dimensions. If everything is working so far, a map will appear with dots for all your coordinates. Neat! Now to turn those dots into lines, under “Marks” click the drop down menu and select “lines.” You will now get a map with a line connecting all your points.
Drag your unique identifier into “path” and your common identifier into “detail,” colour, or anything else you might want to represent. This will ensure that each “pair” of coordinates gets only one line. Here’s mine.
Anyone interested in flow mapping and HGIS and looking for more guidance, collaboration, or information should feel free to contact me at the Sherman Center.
I am very grateful to the support of the Sherman Centre for providing the software, hardware, and financial/educational support for this project.