Since 2001, the number of immigrants arriving in the city of Toronto, in the Canadian province of Ontario, has been fluctuating, but overall increasing. There were slightly more than 123,000 people immigrating to the city in 2001, compared to almost 160,000 twenty years later.
Toronto is the Canadian city with the highest number of immigrants arriving, followed by Vancouver.

Between 2006 and 2023, the level of employment in Toronto, in the province of Ontario, Canada, has fluctuated, but overall increased. There were approximately ********* people employed in 2006, compared to ********* 17 years later. By 2023, the industry that employed the most people in the metropolitan area of Toronto was wholesale and retail trade, with over ******* people employed.

Between July 1, 2021 and June 30, 2022, more than 70 percent of the immigrants arriving in the city of Toronto, in the Canadian province of Ontario, were between the ages of 20 and 44. People between the ages of 25 and 29, in particular, were the most numerous among the immigrant population, at 43,955. During the same period, there were 12,625 immigrants arriving in Toronto.

Context

With a population just short of 3 million people, the city of Toronto is the largest in Canada, and one of the largest in North America (behind only Mexico City, New York and Los Angeles). Toronto is also one of the most multicultural cities in the world, making life in Toronto a wonderful multicultural experience for all. More than 140 languages and dialects are spoken in the city, and almost half the population Toronto were born outside Canada.It is a place where people can try the best of each culture, either while they work or just passing through. Toronto is well known for its great food.

Content

This dataset was created by doing webscraping of Toronto wikipedia page . The dataset contains the latitude and longitude of all the neighborhoods and boroughs with postal code of Toronto City,Canada.

Context

This is modified dataset combining MCI and Homicide

Sources

Unemployment rate: https://www.statista.com/statistics/578362/unemployment-rate-canada/

Police data: http://data.torontopolice.on.ca/pages/open-data

Population data and analysis: see percapita.ipynb Population of toronto: https://en.wikipedia.org/wiki/Demographics_of_Toronto

For 2017: https://www.google.com/publicdata

For 2018: https://www.toronto.ca/city-government/data-research-maps/toronto-at-a-glance/

Average Income: Canadian Mortgage and Housing Company, https://www.cmhc-schl.gc.ca/en/corp/about/cahoob/data/upload/Table-17_EN_Before-Tax_w.xlsx

Neighborhoods map data https://www.toronto.ca/city-government/data-research-maps/open-data/

People experiencing homelessness have historically had high mortality rates compared to housed individuals in Canada, a trend believed to have become exacerbated during the COVID-19 pandemic. In this matched cohort study conducted in Toronto, Canada, we investigated all-cause mortality over a one-year period by following a random sample of people experiencing homelessness (n = 640) alongside matched housed (n = 6,400) and low-income housed (n = 6,400) individuals. Matching criteria included age, sex-assigned-at-birth, and Charlson comorbidity index. Data were sourced from the Ku-gaa-gii pimitizi-win cohort study and administrative databases from ICES. People experiencing homelessness had 2.7 deaths/100 person-years, compared to 0.7/100 person-years in both matched unexposed groups, representing an all-cause mortality unadjusted hazard ratio (uHR) of 3.7 (95% CI, 2.1–6.5). Younger homeless individuals had much higher uHRs than older groups (ages 25–44 years uHR 16.8 [95% CI 4.0–70.2]; ages 45–64 uHR 6.8 [95% CI 3.0–15.1]; ages 65+ uHR 0.35 [95% CI 0.1–2.6]). Homeless participants who died were, on average, 17 years younger than unexposed individuals. After adjusting for number of comorbidities and presence of mental health or substance use disorder, people experiencing homelessness still had more than twice the hazard of death (aHR 2.2 [95% CI 1.2–4.0]). Homelessness is an important risk factor for mortality; interventions to address this health disparity, such as increased focus on homelessness prevention, are urgently needed.

Between July 1, 2021 and June 30, 2022, more than 21,300 people left the city of Toronto, in the Canadian province of Ontario, for other provinces than came to Toronto. This is the second time since 2014/2015 that the interprovincial migration balance is negative. However, this balance of migration had remained negative between 2003/2004 and 2014/2015. In 2021/2022, there were 159,679 immigrants arriving in Toronto.

In 2023, the city of Toronto, in the Canadian province of Ontario had a workforce of over *** million. The industry that employed the most people was wholesale and retail trade, with over ******* people employed, followed by professional, scientific, and technical services. The industries that employed the fewest people were agriculture, forestry, fishing, mining, quarrying, and oil and gas extraction.

In 2022, the average age of the population of the city of Toronto, in the province of Ontario, Canada, was **** years, just over four years higher than in 2001. The average age of the population actually increased relatively steadily between 2001 and 2022. The average age of a population is the mean age of the people in that population. It is different from the median age, which divides the population into two numerically equal groups (one half of the population is younger than the median age, the other is older). In 2022, the median age in Toronto was **** years.

Dataset

This dataset was created by Ali Hasnain

Released under CC0: Public Domain

Contents

In 2022, in Toronto, in the Canadian province of Ontario, 11.6 percent of the population with employment income earned less than 5,000 Canadian dollars, while those earning more than 100,000 Canadian dollars represented 16.6 percent of the population.In 2023, there were more than 3.7 million people employed in Toronto, and the industry that employed the largest number of people was wholesale and retail trade.

For Reference Period 2008: Martin Prosperity Institute, Year 2010 data. The Cultural Location Index (CLI) is an economic indicator that shows the intersection of where people who work in culture occupations live and work, and cultural facilities. This indicator was developed to provide a quantifiable city-wide view of the geographic concentration of Toronto's cultural sector. This indicator is positively influenced in part by the physical presence of cultural facilities, and the concentration of the people who live and work in the cultural sector. The indicator does not capture culture as a set of community values or beliefs. As such a community could have a very active cultural life, and be lower on the Cultural Location Index. The Cultural Location Index (CLI) was produced by the Martin Prosperity Institute for the City of Toronto in 2010. For Reference Period 2011: Data not yet available. For Reference Period 2008: Data not available. For Reference Period 2011: Statistics Canada, 2011 Census, language tables; calculations performed by City of Toronto, Social Policy Analysis & Research (contact spar@toronto.ca). The Linguistic Diversity Index (LDI) is the probability that any two people selected at random would have different mother tongues. Calculated using Greenberg's Linguistic Diversity Index. Lower values mean less diversity, higher values mean more diversity. The Linguistic Diversity Index (LDI) was developed by the City of Toronto, Social Policy Analysis & Research, based on Census 2011 data.

Demographics (2006 and 2011 Census Data) This dataset contains three worksheets. The full description for each column of data is available in the first worksheet called "IndicatorMetaData". The data came from the 2006 and 2011 Census. Some of the data from the 2011 Census was not available at the time of publishing. Refer to the descriptions in worksheet 1 for more information. Users should note that the data for each neighbourhood are based on the mathematical aggregation of smaller sub-areas (in this case Census Tracts) that when combined, define the entire neighbourhood. Since smaller areas may have their values rounded or suppressed (to abide by Statistics Canada privacy standards), the overall total may be undercounted. Population Total (2016 Census Data) The data refers to Total Population from the 2016 Census, aggregated by the City of Toronto to the City's 140 Neighbourhood Planning Areas. Although Statistics Canada makes a great effort to count every person, in each Census a notable number of people are left out for a variety of reasons. For Census 2016: Population and Dwellings example, people may be travelling, some dwellings are hard to find, and some people simply refuse to participate. Statistics Canada takes this into account and for each Census estimates a net 'undercoverage' rate for the urban region, the Toronto Census Metropolitan Area (CMA), but not for the city. The 2011 rate for the Toronto CMA was 3.72% plus or minus 0.53%. The 2016 rate is not yet available

The statistics contained in this dataset were included in the Annual Human Rights Office Report for the Executive Committee and City Council. The full report is available on the City's Web site at http://app.toronto.ca/tmmis/index.do

Starting in January 2017, Toronto Public Health (TPH) began tracking the deaths of people experiencing homelessness to get a more accurate estimate of the number of deaths and their causes. TPH leads the data collection, analysis and reporting. The Shelter, Support and Housing Administration (SSHA) and health and social service agencies that support people experiencing homelessness share information about a death with TPH and the Office of the Chief Coroner of Ontario (OCCO) verifies some of the data. For this data collection initiative, homelessness is defined as “the situation of an individual or family without stable, permanent, appropriate housing, or the immediate prospect, means and ability of acquiring it”.

Income of individuals by age group, sex and income source, Canada, provinces and selected census metropolitan areas, annual.

The dataset contains residential property prices in different regions of Greater Toronto area, Canada. The data was scraped from the website https://realtor.ca in March 2022.

Canada's largest metropolitan area is Toronto, in Ontario. In 2022. Over 6.6 million people were living in the Toronto metropolitan area. Montréal, in Quebec, followed with about 4.4 million inhabitants, while Vancouver, in Britsh Columbia, counted 2.8 million people as of 2022.

The Census of Population is held across Canada every 5 years and collects data about age and sex, families and households, language, immigration and internal migration, ethnocultural diversity, Aboriginal peoples, housing, education, income, and labour. City of Toronto Neighbourhood Profiles use this Census data to provide a portrait of the demographic, social and economic characteristics of the people and households in each City of Toronto neighbourhood. The profiles present selected highlights from the data, but these accompanying data files provide the full data set assembled for each neighbourhood. For an interactive visualization of this data, visit the Neighbourhood Profiles webpage. In these profiles, "neighbourhood" refers to the City of Toronto's 158 social planning neighbourhoods. These social planning neighbourhoods were developed in the late 1990s by the City of Toronto to help government and community organizations with local planning by providing socio-economic data at a meaningful geographic area. The boundaries of these social planning neighbourhoods are consistent over time, allowing for comparison between Census years. Neighbourhood level indicators from sources other than the Census of Population are also available through the City's Wellbeing Toronto mapping application and here on the Open Data portal. Each data point in this file is presented for the City's 158 neighbourhoods or 140 neighbourhoods prior to April 2021. The data is sourced from a number of Census tables released by Statistics Canada. The general Census Profile is the main source table for this data. Data tables are available for the Census years of 2001, 2006, 2011, 2016, and 2021. For definitions of terms and concepts referenced in this data set, as well as limitations imposed by rounding, data suppression standards, and geometry, users should consult the reference materials produced by Statistics Canada for the 2016 Census or the 2021 Census. Please note that social planning neighbourhoods are not an official standard geography produced by Statistics Canada and the data herein is compiled by special request through the Community Data Program.

The Canadian Cuisine Photography Challenge is a pilot experiential learning activity created at Ryerson University for the class FNU100-Canadian Cuisine: Historical Roots, a first/second year liberal studies course offered to students from diverse programs and cultural backgrounds. This activity is both a fun challenge and a required course assignment. It aims to engage students with Canadian cuisine and is inspired by a decolonial pedagogical approach (Mignolo & Walsh, 2018; Santos, 2018) to food studies, and elements of photovoice methodology (Wang & Burris, 1997). The Canadian Cuisine Photography Challenge consists of a field trip to different food places or sitopias in Toronto with the goal of learning about their histories and developing an appreciation of the role of food and people in the city (Newman, 2017). The activity includes a map, instructions and a set of ten challenge questions that students answer through photographs taken during their field trip. The field trip is followed by students’ presentations in class and a reflection of their experiences. In the first phase of the project, students explored two sitopias: Kensington Market and Chinatown. This paper will first describe the co-creation of the Canadian Cuisine Photography Challenge with students from the School of Nutrition at Ryerson University. This was a collaboration between the course instructor, two School of Nutrition students and included input from other students who had previously taken the course. It will present key learnings from the feedback of students who participated in the challenge in the fall of 2019, including how they described their experience, what they learned and suggestions for the future developments of this project. In particular this field reportwill discuss the use of a decolonial pedagogy in food studies, recognizing and challenging a Western hegemonic view of food places as representative of Canadian cuisine, while at the same time outlining the co-construction of experiential learning activities to engage students and provide content that reflects the multiple identities and food cultures of Canadians in Toronto. The main purpose of this field report is to share our experience co-creating and implementing this pilot project as one contribution towards decolonial food pedagogies.