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All (5)

All (5) ((5 results))

  • 1. Need for Speed: Using fastText (Machine Learning) to Code the Labour Force Survey Archived
    Articles and reports: 11-522-X202100100013
    Description: Statistics Canada’s Labour Force Survey (LFS) plays a fundamental role in the mandate of Statistics Canada. The labour market information provided by the LFS is among the most timely and important measures of the Canadian economy’s overall performance. An integral part of the LFS monthly data processing is the coding of respondent’s industry according to the North American Industrial Classification System (NAICS), occupation according to the National Occupational Classification System (NOC) and the Primary Class of Workers (PCOW). Each month, up to 20,000 records are coded manually. In 2020, Statistics Canada worked on developing Machine Learning models using fastText to code responses to the LFS questionnaire according to the three classifications mentioned previously. This article will provide an overview on the methodology developed and results obtained from a potential application of the use of fastText into the LFS coding process. 

    Key Words: Machine Learning; Labour Force Survey; Text classification; fastText.

    Release date: 2021-11-05
  • 2. The cancer survival index: Measuring progress in cancer survival to help evaluate cancer control efforts in Canada
    Articles and reports: 82-003-X202100900002
    Description:

    This study is the first comprehensive evaluation of progress in cancer survival for all cancer types combined in Canada. The results span the complete time period of the Canadian Cancer Registry and are unaffected by changes in the age, sex and case-mix of cancers over this time. Specifically, predicted Canadian net cancer survival index (CSI) estimates for the three-year period from 2015 to 2017 are presented and compared with corresponding actual estimates dating as far back as the 1992-to-1994 period. Comparisons are made for both sexes combined and for males and females separately. Further insight is provided by the determination of the most influential cancer and sex combinations and the leading cancer types within each sex, in regard to changes in the CSI since the periods of 1992 to 1994 and 2005 to 2007.

    Release date: 2021-09-15
  • 3. Stats are on the menu! Canada’s restaurant industry Archived
    Stats in brief: 11-627-M2021025
    Description:

    This infographic highlights a selection of statistics on restaurants, bars and caterers in Canada.

    Release date: 2021-03-25
  • 4. Association between Food Insecurity and Stressful Life Events among Canadian Adults
    Articles and reports: 89-648-X2021001
    Description:

    This study investigates the extent to which stressful life events may increase the likelihood of food insecurity among the Canadian adult population. Data from the Wave 4 (2018) of the Longitudinal and International Study of Adults (LISA) and multivariable logistic models were used for the analyses, taking into account the complex survey design and adjusting for other socio-demographic and socio-economic variables known to be associated with food insecurity. The results show that work and health-related stressful life events significantly increase the likelihood of exposure to food insecurity. The results also show that adults who reported having two or more stressful life events were about four times more likely to experience food insecurity than those who reported zero stressful life events.

    Release date: 2021-03-10
  • 5. Trends in paediatric cancer survival in Canada, 1992 to 2017
    Articles and reports: 82-003-X202100200001
    Description:

    This study describes survival, improvement in survival over time and conditional survival for paediatric cancer patients in Canada.

    Release date: 2021-02-17
Stats in brief (1)

Stats in brief (1) ((1 result))

Articles and reports (4)

Articles and reports (4) ((4 results))

  • 1. Need for Speed: Using fastText (Machine Learning) to Code the Labour Force Survey Archived
    Articles and reports: 11-522-X202100100013
    Description: Statistics Canada’s Labour Force Survey (LFS) plays a fundamental role in the mandate of Statistics Canada. The labour market information provided by the LFS is among the most timely and important measures of the Canadian economy’s overall performance. An integral part of the LFS monthly data processing is the coding of respondent’s industry according to the North American Industrial Classification System (NAICS), occupation according to the National Occupational Classification System (NOC) and the Primary Class of Workers (PCOW). Each month, up to 20,000 records are coded manually. In 2020, Statistics Canada worked on developing Machine Learning models using fastText to code responses to the LFS questionnaire according to the three classifications mentioned previously. This article will provide an overview on the methodology developed and results obtained from a potential application of the use of fastText into the LFS coding process. 

    Key Words: Machine Learning; Labour Force Survey; Text classification; fastText.

    Release date: 2021-11-05
  • 2. The cancer survival index: Measuring progress in cancer survival to help evaluate cancer control efforts in Canada
    Articles and reports: 82-003-X202100900002
    Description:

    This study is the first comprehensive evaluation of progress in cancer survival for all cancer types combined in Canada. The results span the complete time period of the Canadian Cancer Registry and are unaffected by changes in the age, sex and case-mix of cancers over this time. Specifically, predicted Canadian net cancer survival index (CSI) estimates for the three-year period from 2015 to 2017 are presented and compared with corresponding actual estimates dating as far back as the 1992-to-1994 period. Comparisons are made for both sexes combined and for males and females separately. Further insight is provided by the determination of the most influential cancer and sex combinations and the leading cancer types within each sex, in regard to changes in the CSI since the periods of 1992 to 1994 and 2005 to 2007.

    Release date: 2021-09-15
  • 3. Association between Food Insecurity and Stressful Life Events among Canadian Adults
    Articles and reports: 89-648-X2021001
    Description:

    This study investigates the extent to which stressful life events may increase the likelihood of food insecurity among the Canadian adult population. Data from the Wave 4 (2018) of the Longitudinal and International Study of Adults (LISA) and multivariable logistic models were used for the analyses, taking into account the complex survey design and adjusting for other socio-demographic and socio-economic variables known to be associated with food insecurity. The results show that work and health-related stressful life events significantly increase the likelihood of exposure to food insecurity. The results also show that adults who reported having two or more stressful life events were about four times more likely to experience food insecurity than those who reported zero stressful life events.

    Release date: 2021-03-10
  • 4. Trends in paediatric cancer survival in Canada, 1992 to 2017
    Articles and reports: 82-003-X202100200001
    Description:

    This study describes survival, improvement in survival over time and conditional survival for paediatric cancer patients in Canada.

    Release date: 2021-02-17
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