Making Muskoka: Tourism, Rural Identity, and Sustainability, 1870–1920 by Andrew Watson (review)
Bibliographic record
Abstract
Reviewed by: Making Muskoka: Tourism, Rural Identity, and Sustainability, 1870–1920 by Andrew Watson Peter A. Stevens Watson, Andrew – Making Muskoka: Tourism, Rural Identity, and Sustainability, 1870–1920. Vancouver: UBC Press, 2022. 280 p. Tourism history tends to privilege the activities and perspectives of travellers and promoters, with the experiences of local populations going unexamined. No such criticisms can be made of Andrew Watson's new book. Muskoka, situated 150 kilometres north of Toronto, is one of Canada's famed tourism regions; its [End Page 232] emergence during the late nineteenth century as a site of lavish lakeside hotels and summer homes has been recounted in both scholarly works and numerous popular histories. Making Muskoka turns this familiar story on its head by focusing on the Indigenous people and non-Indigenous settlers who made tourism possible in Muskoka. In addition, it highlights the material realities that have shaped human relationships with this iconic landscape. Watson is particularly interested in the socio-economic and environmental conditions that gave rise to tourism in Muskoka. The concepts of rural identity and sustainability are central to his analysis. Noting that scholars often take "rural" simply as a synonym for "agricultural," Watson shows that in Muskoka, farming combined with other forms of economic activity to create a distinct, multi-dimensional rural identity. Moreover, this identity arose not just from social interactions, but through engagement with a specific material environment, and it evolved over time. As circumstances changed, the various dimensions of rural identity in Muskoka became more or less sustainable, with sustainability here referring to "the potential for a society… to reproduce patterns of economic exchange, social relationships, and environmental conditions" (p. 12). As Watson explains, Euro-Canadians began settling in Muskoka around the time of Confederation. Impressed by the region's forests, governments offered free land grants to aspiring farmers, confident that they could extend the ordered, agrarian society that was taking root in what is now southern Ontario. Almost immediately, however, the environmental realities of the Canadian Shield served to frustrate these plans. Muskoka was a patchwork of lakes, swamps, and rocky outcroppings, and where arable land did exist, the soils were poor. Many would-be farmers soon abandoned their lands, and those who remained were forced to find alternative sources of income. Adopting a strategy of "occupational pluralism" (p. 5), they hunted and fished, and took part-time work related to forestry and, especially, tourism. Indeed, Watson argues, tourism's co-evolution alongside farming and logging during the first generation of Euro-Canadian settlement granted Muskoka a rural identity that was distinct in North America. The same environmental features that made Muskoka unsuitable for farming made the region attractive to the wealthy, leisured classes in the cities of southern Ontario and the north-eastern United States. The first tourists and the first settlers came to Muskoka concurrently, and after the railway arrived in the 1870s, luxurious hotels and private summer homes mushroomed around the region's lower lakes. Tourism was a boon to Muskoka's struggling settlers, although they benefited unevenly, as Watson observes. Those who owned lakeside property built hotels or sold off lots for cottage development, transforming their marginal farms into flourishing resorts. Some even launched steamboat enterprises that transported tourists, or delivered local food and other provisions to isolated hotels and cottages. Settlers whose property was located in the backwoods were less fortunate, although some produced goods that they then sold to tourists, such as fruit and vegetables, meat, eggs and dairy products, and cordwood. Watson identifies forestry as a further aspect of rural identity in Muskoka. During the last three decades of the nineteenth century, many settlers spent part of [End Page 233] the year harvesting white pine for sawmills, and hemlock bark for local tanneries, which used it as a dyeing agent. These large-scale forestry operations damaged the ecology and moved on once the desired trees had been harvested, so the benefits to locals, though significant, were short-lived. More sustainable were the small-scale techniques that settlers used to harvest wood resources on their own properties, an approach that caused less environmental harm and endured long after commercial operations had ceased. Of course, Muskoka...
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".