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TwitterNumber of employees by class of worker, North American Industry Classification System (NAICS) and gender, annual.
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TwitterNumber of employees by class of worker and gender. Data are also available for the standard error of the estimate, the standard error of the month-to-month change and the standard error of the year-over-year change.
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Twitterhttps://www.statcan.gc.ca/en/reference/licencehttps://www.statcan.gc.ca/en/reference/licence
Labour Force Survey The Labour Force Survey provides estimates of employment and unemployment which are among the timeliest and important measures of performance of the Canadian economy. The LFS estimates are the first of the major monthly economic data series to be released. The Canadian Labour Force Survey was developed following the Second World War to satisfy a need for reliable and timely data on the labour market. Information was urgently required on the massive labour market changes involved in the transition from a war to a peace-time economy. Objective The main objective of the LFS is to divide the working-age population into three mutually exclusive classifications - employed, unemployed, and not in the labour force - and to provide descriptive and explanatory data on each of these. LFS data are used to produce the well-known unemployment rate as well as other standard labour market indicators such as the employment rate and the participation rate. The LFS also provides employment estimates by industry, occupation, public and private sector, hours worked and much more, all cross-classifiable by a variety of demographic characteristics. Estimates are produced for Canada, the provinces, the territories and a large number of sub-provincial regions. For employees, wage rates, union status, job permanency and workplace size are also produced. These data are used by different levels of government for evaluation and planning of employment programs in Canada. Regional unemployment rates are used by Employment and Social Development Canada to determine eligibility, level and duration of insurance benefits for persons living within a particular employment insurance region. The data are also used by labour market analysts, economists, consultants, planners, forecasters and academics in both the private and public sector. Collection This public use microdata file contains non-aggregated data for a wide variety of variables collected from the Labour Force Survey (LFS). It contains both personal characteristics for all individuals in the household and detailed labour force characteristics for household members 15 years of age and over. The personal characteristics include age, sex, marital status, educational attainment, and family characteristics. Detailed labour force characteristics include employment information such as class of worker, usual and actual hours of work, employee hourly and weekly wages, industry and occupation of current or most recent job, public and private sector, union status, paid or unpaid overtime hours, job permanency, hours of work lost, job tenure, and unemployment information such as duration of unemployment, methods of job search and type of job sought. Labour force characteristics are also available for students during the school year and during the summer months as well as school attendance whether full or part-time and the type of institution. LFS revisions: Labour force surveys are revised on a periodic basis. The most recent revisions took place in 2025. As of January 2025, LFS microdata and estimates have been adjusted to reflect population counts from the 2021 Census, with revisions going back to 2011. Additionally, several changes were made to key variables on the PUMFs: Survey weights (FINALWT) have been updated to use 2021 Census population control totals. Sub-provincial geography (CMA) has been updated to the 2021 Standard Geographical Classification (SGC) boundaries. All industry data (NAICS_21) was revised to use the latest standard, North American Industry Classification System (NAICS) 2022. Coding enhancements were applied to improve longitudinal consistency of detailed National Occupational Classification data (NOC_10 and NOC_43). Data were revised to use the gender of person instead of sex (GENDER).
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TwitterOpen Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
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The 2020 Public Service Employee Survey (PSES) was administered by Advanis, on behalf of the Office of the Chief Human Resources Officer, Treasury Board of Canada. This comprehensive survey measured federal government employees’ opinions about their engagement, leadership, workforce, workplace, workplace well-being, compensation, diversity and inclusion, and the impacts of COVID-19. The 2020 Public Service Employee Survey was conducted from November 30, 2020 to January 29, 2021. A total of 188,786 employees in 87 federal departments and agencies responded to the 2020 Public Service Employee Survey, for a response rate of 61%. The 2020 Public Service Employee Survey datasets contain the results of the survey by year (2020, 2019 and 2018) for the Public Service and departments/agencies, and the results broken down by demographic characteristics (e.g., age, gender) and organizational units. Results for 2019 and 2018 are only provided for questions repeated in the 2020 Public Service Employee Survey.
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TwitterNumber of days lost per full-time employee in a year, by public and private sector and gender, annual.
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TwitterOpen Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
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The 2017 Public Service Employee Survey (PSES) was led by the Office of the Chief Human Resources Officer (Treasury Board of Canada Secretariat), in collaboration with Statistics Canada. The 2017 Public Service Employee Survey measured federal public servants’ opinions in relation to employee engagement, leadership, the workforce, the workplace, workplace well-being and compensation. The 2017 Public Service Employee Survey was conducted from August 21 to September 29, 2017. A total of 174 544 employee in 86 federal departments and agencies responded to the survey, for a response rate of 61.3%. The 2017 Public Service Employee Survey datasets contain the results of the survey by year (2017, 2014, 2011 and 2008) for the Public Service and departments/agencies, and the results broken down by demographic characteristics (e.g., age, gender) and organizational units. Results for 2014, 2011 and 2008 are only provided for questions repeated in the 2017 Public Service Employee Survey. Notice of correction: Results broken down by organizational units in Employment and Social Development Canada have been revised and updated on August 22, 2018.
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TwitterProportion of women and men employed in the National Occupational Classification (NOC) broad occupational categories, current year.
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TwitterOpen Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
License information was derived automatically
The 2017 Public Service Employee Survey (PSES) was led by the Office of the Chief Human Resources Officer (Treasury Board of Canada Secretariat), in collaboration with Statistics Canada. The 2017 Public Service Employee Survey measured federal public servants’ opinions in relation to employee engagement, leadership, the workforce, the workplace, workplace well-being and compensation. The 2017 Public Service Employee Survey was conducted from August 21 to September 29, 2017. A total of 174 544 employee in 86 federal departments and agencies responded to the survey, for a response rate of 61.3%. The 2017 Public Service Employee Survey datasets contain the results of the survey by year (2017, 2014, 2011 and 2008) for the Public Service and departments/agencies, and the results broken down by demographic characteristics (e.g., age, gender) and organizational units. Results for 2014, 2011 and 2008 are only provided for questions repeated in the 2017 Public Service Employee Survey. Notice of correction: Results broken down by organizational units in Employment and Social Development Canada have been revised and updated on August 22, 2018.
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TwitterAverage percentage of women and men in management positions, by North American Industry Classification System (NAICS), business employment size, type of business, business activity and majority ownership, first quarter of 2025.
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TwitterOpen Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
License information was derived automatically
Data on employment income statistics by industry sectors (2-digit code) from the North American Industry Classification System (NAICS) 2017, Indigenous identity, highest level of education, work activity during the reference year, age and gender, for the population aged 15 years and over who reported weeks worked and employment income in 2020 in private households in Canada, provinces and territories, census metropolitan areas and census agglomerations with parts.
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TwitterNumber of persons in the labour force (employment and unemployment) and unemployment rate, by North American Industry Classification System (NAICS), gender and age group.
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TwitterEmployment estimates by class of worker, gender, and visible minority group.
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TwitterData on employment income statistics, by occupation minor group (4-digit code) from the National Occupational Classification (NOC) 2021, immigrant status and period of immigration, highest level of education, work activity during the reference year, age and gender, for the population aged 15 years and over who reported weeks worked and employment income in 2020 in private households in Canada, provinces and territories.
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TwitterData on police officers (by high level ranks and gender), total number of civilian personnel, special constables and recruits (each by gender). The proportion of total police, civilians, special constables and recruits from total personnel, and also the proportion of high level ranks from total number of police officers. Data is provided for municipal police services, 2000 to 2023.
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TwitterAnnual counts of enterprises by gender (men+, women+) of owner and enterprise size.
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TwitterNumber of employees by union status, North American Industry Classification System (NAICS) and gender.
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TwitterAverage hourly and weekly wage rate, and median hourly and weekly wage rate by National Occupational Classification (NOC), type of work, gender, and age group.
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TwitterRetirement age by class of worker and gender, annual.
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TwitterNumber of employees by class of worker, North American Industry Classification System (NAICS) and gender, annual.