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Montréal Streets clusters

Living together

This map shows relationships between where people lived and what they did for a living.Clusters of occupationsi reflect residential choices. Since most people tried to keep their commute as short as possible, they tended to live close to the workplace. Likewise, many shops and factories were located close to their suppliers or customers.

At mid-century, Montréal was a commercial city with neighbourhoods defined by a single variable: occupational status. While some street clusters were primarily home to rich and prestigious merchants and lawyers (red or orange dots), others were dominated by hard-pressed labourers and wharfingers (blue dots). Why did the poor live on the periphery? Who could afford to live in the centre of town?

By 1861, some occupations had moved up the hill to newer parts of the city. Industrialization had begun to define neighbourhoods according to the work done by their residents. The nail and engine factories required one set of skills, the shoe factories another. Other occupations—tobacconists, hotelkeepers, printers, night watchmen, etc.—remained clustered in the centre of town.

By 1881, Montréal neighbourhoods had become even more differentiated. Streets of the same color share a distinctive profile of occupations. The green and blue dots in the south of town correspond to concentrations of metal workers in low-rent streets. Whereas some high-rent clusters were centrally located along high-traffic streets, others corresponded to areas of low-density housing with gardens. Street clusters defined strictly in terms of occupations reflect social characteristics as well, such as language and ethnic origin.

In 1901, Montréal was home to ten times as many people as in 1848. We have sorted these residents into 20 distinct occupational profiles. The grouping of streets is again based solely on similarity of occupations present, but we discover other social differences. Of the three richest clusters of streets (the red dots), one is occupied by an older generation living in older buildings, another is dominated by younger managers and accountants living in a new suburb, and a third cluster is an emerging university district of French-speaking professionals.

Distinguishing properties of street clusters in 1848

Distinguishing properties of street clusters in 1861

Distinguishing properties of street clusters in 1881

Distinguishing properties of street clusters in 1901


Living together's clusters of occupations

We generated clusters by identifying occupations that appeared in the same streets and streets that were home to a distinctive profile of occupations. Then, we mapped the streets (at their midpoints) and coloured them according to their occupational profiles.

The profiles of streets in the same group are not identical, but they are similar. The maps therefore show where certain types of worker lived (or didn’t live), and which occupations tended to live close to one another. This provides clues to how the city itself was changing, as new jobs were created and neighbourhoods were transformed, or as residents were attracted to certain areas and avoided others.

The number of groups is arbitrary and the groupings are unique to each year. The same occupations didn’t necessarily share the same streets 20 or 40 years later. But some types of workers, like tavern keepers and peddlers, consistently lived close to one another. Can you find any similar examples?

To avoid jumping to any conclusions in our analysis, we used a strategy called progressive aggregation. Starting with the smallest possible social units—households and occupation titles—we grouped the households into street segments, and then grouped the populations of street-segments into clusters that shared the same occupational profile. At the same time, we identified occupational clusters located on the same streets.

The dots on the maps are based on street segments, the most meaningful unit we could find for analyzing urban neighbourhoods. Nineteenth-century cities had a very fine grain. Similar buildings, similar activities and residents with similar occupations were normally found on opposite sides of the same street. Individual segments cover at least 30 households (the mean number of households per segment was 60 in 1861 and 100 in 1900).

In 1889, when Charles Booth produced his detailed map of London , he used street segments to identify the social status of city residents. As we found in our work on Baltimore and Montréal, and as Olivier Zunz found in his work on Detroit, Booth discovered that “twin block faces” produced more homogeneous units than going “round the block.” (This is often obvious from the sizes of building footprints along the street and its cross streets.)

In more technical terms, we grouped street segments based on the presence or absence of occupations according to Ward’s method, which assigns the same significance to the presence or absence of all occupation titles. (For 1861, we worked with 197 segments and 91 occupation titles). The process was hierarchical and agglomerative. Clusters were created step-by-step by pairing streets whose occupational profiles were most similar. We used an iterative method to retest each segment against its assigned cluster, continuing to make any necessary adjustments until we achieved stable groupings.

For example, many street segments near a nail factory in southwest Montréal consistently included at least one nailmaker, one founder, and one moulder. Although the pattern was not obvious in 1848, this set of streets appeared together as a near-identical cluster in 1861, 1881 and 1901.

Although they were not selected by using any district boundaries, all the resulting street clusters seem to have geographical meaning. We sorted the streets strictly on the basis of their occupational profiles—proximity was not a criterion. And yet each cluster appears as a cloud of points on the map, revealing its neighbourhood character.

We found that streets in a cluster based on occupational profile often shared other properties, such as distance from the centre of town, rent level and the cultural background of residents. In particular, the street segments in the highest rent cluster ($150 annual median rent) had very similar professional profiles and occupied low-density housing on the city’s 30-metre terrace and on the slope of Mount Royal, with a largely English-speaking population and a small core of French-Canadian professionals in the east. A separate cluster contains the streets surrounding that core, with median rents of about $100 per year. These two high-rent clusters trace classic wedges extending out from the original walled city on the riverfront.

The groupings shift a little in later years, but there is always a high-rent cluster with the same characteristics. The colour codes provide cues to continuities from one decade to the next. Regardless of the date, when looking at St. Ann’s Ward, you can distinguish a newer zone from an older one defined by occupations that tended to seek out the centre of town. In 1861, one cluster shows a distinctive set of lanes around the railway station. They would soon be torn down to make way for the expanding railway facilities.

You can identify specific clusters based on one or two “diagnostic” occupations. In 1861, for example, about a third of residents in the “plumber cluster” had an on-site workplace or business. The wide range of rents and the somewhat higher median rents imply that these households had a little more space. This does not mean, of course, that everybody paid high rents. The same streets had highly educated doctors, wealthy watchmakers and jewellers, poor barbers and bookbinders, as well as small entrepreneurs such as confectioners, tobacconists, boardinghouse keepers, and milliners. Many residents combined a skill or service with a retail shop. Other examples from 1861 include an “engineer cluster” and a “stonecutter cluster” located on the edge of town.

Each period also features a distinctive city-building sector out on the edge of town. Some of the residents were doing the construction work: roofers, plasterers, masons, carpenters, and painters. Some residents were part of the city’s “halo of poverty” living under the constant threat of destruction and ejection. Workers in the building trades were able to achieve high rates of homeownership, and large number of French Canadians found they provided an important path to upward mobility, despite the risk of financial failure along the way. Thus, many moved from an artisanal role to become a proprietor, a capitalist, or the resident owner of a duplex.

In the early stage of the industrialization of Montréal (1848–1861), each set of occupations helped shape the city’s dynamic structure: the merchants secluded themselves in the suburbs, the petite bourgeoisie focused on developing institutions, the traders in the central business district, the engineering and mechanical trades on the industrial frontier, the builders and craftsmen on the perimeter. Irish carters crowded into the lanes between St. Patrick’s Church and the railroad station, and French-Canadian shoe workers, concentrated in crowded conditions, produced higher volumes and generating higher profits. Are the same processes visible in 1881 and in 1901? Are the same occupations living and working alongside one another? How did a new city take shape as new immigrant groups arrived, new neighbourhoods were built, and new occupations emerged?

In nature, the distribution of species follows various environmental gradients, since different species are adapted to different conditions. For example, moisture levels, the risk of frost and the length of the growing season all affect the likelihood of finding a particular plant in a particular place. Montrealers planted apple orchards and market gardens on the sunny south-facing slope of Mount Royal. So what gradients affected the distribution of Montréal workers? Land values show that proximity to the centre of town was the most powerful gradient. Elevation was also meaningful. Status, entrepreneurship, and industrial linkages all played key roles in determining social choices and patterns of co-residence.

In 1848, status was the strongest dimension. The rich lived in the centre of town and the poor lived on the periphery, although nobody lived very far from anybody else. The changes that occurred over the following decades point to features of “social mobility”. Distinctions between neighbourhoods based on social status remain very strong today, and they have been consistently recognized in historical geographies of other cities. In Montréal, few individuals achieved a higher status during their own lifetime. Such short-term upward mobility was most common among storekeepers. On average, families did tend to improve their status from one generation to the next, as reflected in where they chose to live.

The city was multidimensional, and over time other dimensions emerged as important, including language, religion, and place of origin.

When we analyzed the data, we were surprised by the degree to which the occupational profiles of low-rent “popular” communities became more differentiated over the half-century. Reflected in the language used by workers to describe their occupations, this differentiation appears to have been based on the location of various industrial activities: along the waterfront, the canal, the post-road, or the railway; near certain other industries; or close to the centre of town, home to financial institutions and head offices.

In the 1840s, although the poor were spread out along the periphery, as far as two kilometres from the centre of town, the east and west ends of city had similar occupational profiles. By 1861, however, east-west differences were obvious, and by the end of the century the north end had its own distinctive profile. In the 1850s, industrialization created concentrations of metal workers, whose numbers expanded relative to woodworkers and leatherworkers. These trades interacted and were associated with shipyards and railway shops. As tracks encircled the city, the shops in Montréal began to service transcontinental railways, generating a band of related occupations.

Spectacular business growth—combined with the mobility of some parts of the working class, obsolescence, as well as external factors like traffic, noise, and pollution—left older districts ripe for receiving immigrants from abroad and newcomers from the villages surrounding the city.

Two centres of “implosion” correspond to clusters defined by tailors and shoemakers. As late as 1881, merchant tailors were living near the centre of town or along business streets. But by 1901, the city had a classic garment district and an adjacent fur district that closely corresponded to concentrations of Jewish residents and occupations common among Jewish immigrants in the 1890s: peddlers, jewellers, and shopkeepers. The same profile emerged in New York, Philadelphia, Baltimore, and Toronto, where collar and buttonhole makers sought out the benefits of proximity to manufacturers of “readymade” clothing. Like occupations associated with the centre of town, these were characterized by tight control and long hours. Around 1903, this implosion was reflected in a swift reconstruction of loft buildings.

A similar implosion had already occurred in the manufacture of shoes, where intense mechanization took hold by the 1860s. Massive factories employed French Canadian migrants from nearby rural areas. They married young, and like the city’s tailors, they lived on a shoestring during the depressions of the 1870s and the 1890s. Two-storey buildings with two flats each were replaced by three-story triplexes. In terms of people per acre of ground, the density of workers’ housing tripled between 1861 and 1901, but the newly-built working-class flats offered 50% more floor area in the average apartment.



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For additional information or to make suggestions,
contact info@cieq.ca
Sherry Olson
sherry.olson@mcgill.ca
  Dept. of Geography
McGill University
805 Sherbrooke St. W.
Montréal, QC, H3A 0B9
Robert C.H. Sweeny
rsweeny@mun.ca
  Dept. of History
Memorial University
of Newfoundland
St John's TN A1C 5S7
CIEQ
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