Bibliographic record
Abstract
Big cities have always been attractive places for people to settle. However, recent trends, including work-from-home and hybrid work arrangements, along with the rising cost of housing in big cities, mean more Canadians of all age groups are relocating to smaller communities. Much of this movement is to smaller areas within the same province, so that communities which traditionally saw an out-migration of population are now dealing with the challenges createdby a significant influx of new residents. Focusing on the exodus from the three largest Canadian Census Metropolitan Areas (CMAs) of Montreal, Toronto and Vancouver, this paper examines the challenges and consequences for smaller communities. The proportion of people living in these three CMAs has grown from 28.9 per cent in 1981 to35.5 per cent in 2021. This increase reflects the fact that the fastest growing industries, suchas finance, technology and communications, are located in major urban areas. However, the pandemic, combined with the technology that allows people to work from anywhere, means that more people are moving to smaller communities where they can enjoy lower housing costs and other benefits that less dense places offer. While younger people willing to tolerate the occasional commute to the city in hybrid working arrangements are relocating to smaller communities, some retirees are downsizing and also leaving the big city behind. This out-migration has created challenges for big cities. With workers resisting a return to the downtown office, urban cores are left with vast amounts of empty office space. Companies are thus reducing the size of their leased space or not renewing current leases. Public transit and shopping malls have seen usage drop, and a subsequent rise in crime and social disorder in some cities is encouraging even more people to consider moving elsewhere. The COVID-19 pandemic certainly contributed to the increasing exodus from the largest cities.A post-pandemic return to normal economic activity could slow departures from the big cities. The largest CMAs are still growing, due to an increasing number of immigrants, many of whom prefer to settle in big cities where people who arrived previously from their homelands have located. Canada’s commitment to expanded immigration has meant continued growth for major urban centres while the exodus of people from those centres has renewed the growth of mid-size and smaller communities. For the community of Cowansville, Quebec, for example, the flow of people out of Montrealhas produced renewed growth. The newcomers, especially those who bring significant resources with them, stimulate the local economy. Greater demand for products and services helps local businesses and can create employment opportunities for local residents. It will be important to monitor these migration trends in the coming years in order to ensure that infrastructure, funding and services adapt to the challenges so that everyone, whether they choose to live in a big city or in a small community, has access to the services and infrastructure they need in order to enjoy an optimum quality of life.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".