The City of Toronto conducted an online survey from February 22 to March 10, 2017, to seek input from residents and other members of the public to help determine how and when the City makes information available in languages other than English. This survey was conducted as a part of the City's review of the Multilingual Services Policy to ensure it continues to meet the needs of Toronto's diverse communities. The survey was provided in Simplified Chinese, Spanish, Tamil, Tagalog, Italian, Portuguese, Farsi, Urdu, Korean, French, Bengali and Somali. The languages were chosen based on the top spoken languages at home in Toronto as per the 2011 census data, and based on requests received for languages

The City of Toronto conducted an online survey from February 22 to March 10, 2017, to seek input from residents and other members of the public to help determine how and when the City makes information available in languages other than English. This survey was conducted as a part of the City's review of the Multilingual Services Policy to ensure it continues to meet the needs of Toronto's diverse communities. The survey was provided in Simplified Chinese, Spanish, Tamil, Tagalog, Italian, Portuguese, Farsi, Urdu, Korean, French, Bengali and Somali. The languages were chosen based on the top spoken languages at home in Toronto as per the 2011 census data, and based on requests received for languages

Presents socio-demographic information of York Region’s population and is aggregated from Statistics Canada’s Census data. For reference purposes, York Region data is compared to those of Ontario, Canada, the Greater Toronto Area and York Region local municipalities.

This dataset tracks annual reading and language arts proficiency from 2011 to 2022 for Toronto Jr. / Sr. High School vs. Ohio and Toronto City School District

This table is part of a series of tables that present a portrait of Canada based on the various census topics. The tables range in complexity and levels of geography. Content varies from a simple overview of the country to complex cross-tabulations; the tables may also cover several censuses.

A primary goal of the Heritage Language Variation and Change Project (HLVC) is to construct a unique corpus of conversational speech in ten Heritage Languages spoken in the Greater Toronto Area. This corpus, the Heritage Language Documentation Corpus, or HerLD, contains recordings in the Heritage Languages of speakers representing three generations. Our goal is to record 40 speakers, balanced for age and sex, for each of the three generations (and 20 speakers for languages where only two generations exist in Toronto, i.e., Korean and Faetar).

Presents socio-demographic information of York Region’s population and is aggregated from Statistics Canada’s Census data. For reference purposes, York Region data is compared to those of Ontario, Canada, the Greater Toronto Area and York Region local municipalities.

This table is part of a series of tables that present a portrait of Canada based on the various census topics. The tables range in complexity and levels of geography. Content varies from a simple overview of the country to complex cross-tabulations; the tables may also cover several censuses.

This dataset provides a list of instances when Toronto Paramedic Services' Emergency Medical Dispatchers utilized a designated language translation service during medical emergency 9-1-1 calls to provide translation into English. The service allows 9-1-1 callers to access life-saving Paramedic services in over 240 languages.

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.

Abstract Children of Brazilian migrant families in Toronto may be indiscriminately identified as Portuguese-speaking students, an expression used by local school districts mainly in reference to Portuguese-Canadians displaying poor academic achievement. Interviews with students of Brazilian origin who attend schools in one same large School District and their families show, however, different socioeconomic profiles, as indicated by the regions of residence and the occupations of parents, and contrasting language ideologies. Samples of the interviewees' discourse in each profile about the value of speaking Portuguese reveal signs that unskilled migrants are closer to the Portuguese-speaking ethnoclass. The choice to avoid speaking Portuguese by a student in this profile with high academic aspirations reinforces the understanding of various perspectives of what it is to be a Portuguese-speaking student in Toronto. The study reinforces the relevance of social class for contemporary language studies, and contributes to a nuanced characterization of international migrant groups.

This table is part of a series of tables that present a portrait of Canada based on the various census topics. The tables range in complexity and levels of geography. Content varies from a simple overview of the country to complex cross-tabulations; the tables may also cover several censuses.

This data collection is comprised of a one-in-one-hundred sample of persons who completed the long-form census questionnaire (the one-third sample) for the 1976 Census of Canada. To preserve confidentiality, records for this study were selected from geographic areas with populations of 250,000 or more, including Newfoundland, Nova Scotia, New Brunswick, the Montreal census enumeration area, Quebec, the Toronto census enumeration area, Ontario (excluding Toronto), Manitoba, Saskatchewan, Alberta, the Vancouver census enumeration area, and British Columbia (excluding Vancouver). The data have been organized into three separate files by record type: Household, Family, and Individual. Part 1, Household File, contains information on the age, marital status, number, and primary language of household occupants. Part 2, Family File, contains information on age, educational level, languages spoken, children, and population size of place of residence of the husband and wife (or lone parent). Part 3, Individual File, contains detailed information about individual household residents including educational attainment, marital status, employment status, household relationship, language, and sex.

The assertion that artificial intelligence (AI) cannot grasp the complexities of human emotions has been a long-standing debate. However, recent advancements in large language models (LLMs) challenge this notion by demonstrating an increased capacity for understanding and generating human-like text. In this study, we evaluated the empathy levels and the identification and description of emotions by three current language models: Bard, GPT 3.5, and GPT 4. We used the Toronto Alexithymia Scale (TAS-20) and the 60-question Empathy Quotient (EQ-60) questions to prompt these models and score the responses. The models' performance was contrasted with human benchmarks of neurotypical controls and clinical populations. We found that the less sophisticated models (Bard and GPT 3.5) performed inferiorly on TAS-20, aligning close to alexithymia, a condition with significant difficulties in recognizing, expressing, and describing one's or others' experienced emotions. However, GPT 4 achieved performance close to the human level. These results demonstrated that LLMs are comparable in their ability to identify and describe emotions and may be able to surpass humans in their capacity for emotional intelligence. Our novel insights provide alignment research benchmarks and a methodology for aligning AI with human values, leading toward an empathetic AI that mitigates risk.

Presents socio-demographic information of York Region’s population and is aggregated from Statistics Canada’s Census data. For reference purposes, York Region data is compared to those of Ontario, Canada, the Greater Toronto Area and York Region local municipalities.

Multicultural Australian English: The New Voice of Sydney (MAE-VoiS) is a project funded under the Australian Research Council Future Fellowship scheme. The aim of the project is to help us understand the speech patterns of young people from complex culturally and linguistically diverse communities across Sydney. Understanding how adolescents from different ethnicities use speech patterns to symbolically express their diverse sociocultural identities offers a window into understanding a rapidly changing Australian society.

The MAE-VoiS corpus comprises audio recordings of 186 teenagers from 38 language backgrounds who each engaged in a picture naming task and a conversation with a peer facilitated by a local research assistant. Participants also completed an extensive ethnic orientation questionnaire and their parents completed a demographic/language survey. Speakers were located in five separate areas in Sydney that varied according to the dominant language backgrounds of speakers in the communities (four non-English dominant areas – Bankstown, Cabramatta/Fairfield, Inner West, Parramatta; and one English dominant area – Northern Beaches).

The material in this record is a supplement to the corpus. It contains details of the following:

• a picture response task in which 183 single words and 41 short phrases were elicited through a set of images presented on a computer monitor. These items sampled the following characteristics specifically designed to target a wide range of phonetic features known to vary across individuals and groups: all AusE vowels in a targeted consonantal contexts; lexical stress patterns and word internal phonetic/phonological processes through a set of select polysyllabic words; and potential hiatus/juncture contexts through a set of short phrases;
• an Ethnic Orientation Questionnaire (modelled on Hoffman & Walker, 2010 and Clothier, 2019) to measure participants' orientation to their ethnicity, connection to their local community, and use of languages other than English;
• a Demographic survey to determine the child and parent place(s) of birth, gender, and languages spoken (including usage and domains of each language), parents’ age of arrival in Australia (if relevant), parents’ level of education, residence history, siblings and birth order, and whether there was any history of speech, hearing, or language problems/intervention.

Clothier, J. (2019). Ethnolectal variability in Australian Englishes. In L. Willoughby & H. Manns (Eds.), Australian English reimagined: Structure, features and developments (pp. 155–172). Routledge.

Hoffman, M. F., & Walker, J. A. (2010). Ethnolects and the city: Ethnic Orientation and linguistic variation in Toronto English. Language Variation and Change, 22, 37–67.

The Family File gives detailed information on the head and spouse of the census family as well as grouped data on other members of the family. A record, when dealing with the family File, refers to data on one family unit. A family consists of a husband and wife (with or without children who have nevered married, regardless of age) or a parent with one or more children with one or more children never married, living in the same dwelling. A family may also consist of a man or woman living with a gaurdianship or ward under 21 years for whom no pay was received. The "Head of the Family" is the husband in a husband-wife family, or the parent in a one-parent family. This file contains data on the provinces; for data on the CMAs of Montreal and Toronto, see the CMA level file.

This brief thirty-year history of Lexicons of Early Modern English, an online database of glossaries and dictionaries of the period, begins in a fourteenth-floor Robarts Library lab of the Centre for Computing and the Humanities at the University of Toronto in 1986. It was first published freely online in 1996 as the Early Modern English Dictionaries Database. Ten years later, in a seventh-floor lab also in the Robarts Library, it came out as LEME, thanks to support from TAPoR (Text Analysis Portal for Research) and the University of Toronto Press and Library. No other modern language has such a resource. The most important reason for the emergence, survival, and growth of LEME is that its contemporary lexicographers understood their language differently from how we, our many advantages notwithstanding, have conceived it over the past two centuries. Cette brève histoire des trente ans du Lexicons of Early Modern English, une base de données en ligne de glossaires et de dictionnaires de l’époque, commence en 1986 dans le laboratoire du Centre for Computing and the Humanities, au quatorzième étage de la bibliothèque Robarts de l’Université de Toronto. Cette base de données a été publiée gratuitement en ligne premièrement en 1996, sous le titre Early Modern English Dictionnaires Database. Dix ans plus tard, elle était publiée sous le sigle LEME, à partir du septième étage de la même bibliothèque Robarts, grâce au soutien du TAPoR (Text Analysis Portal for Research), de la bibliothèque et des presses de l’Université de Toronto. Aucune autre langue vivante ne dispose d’une telle ressource. La principale raison expliquant l’émergence, la survie et la croissance du LEME est que les lexicographes qui font l’objet du LEME comprenaient leur langue très différemment que nous la concevons depuis deux siècles, et ce nonobstant plusieurs de nos avantages.

The Household File contains housing data as well as some basic demographic information on the occupants of the household. A record, when dealing with the Household File, refers to data on the household unit. A household is a person or groups of persons ocuupying one dwelling. It usually consists of a family group, with or without lodgers, employees, etc. However, it may consist of two or more families sharing a dwelling, or a group of unrelated persons or of one person living alone. This file contains data on the provinces; for data on the CMAs of Montreal and Toronto, see the CMA level file.

Presents socio-demographic information of York Region’s population and is aggregated from Statistics Canada’s Census data. For reference purposes, York Region data is compared to those of Ontario, Canada, the Greater Toronto Area and York Region local municipalities.