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All (18)

All (18) (0 to 10 of 18 results)

  • 1. Measuring Social Capital at the Neighbourhood Level: Experimental Estimates of Sense of Belonging to the Local Community Measured at the Census Tract Level
    Articles and reports: 11-633-X2021007
    Description:

    Statistics Canada continues to use a variety of data sources to provide neighbourhood-level variables across an expanding set of domains, such as sociodemographic characteristics, income, services and amenities, crime, and the environment. Yet, despite these advances, information on the social aspects of neighbourhoods is still unavailable. In this paper, answers to the Canadian Community Health Survey on respondents’ sense of belonging to their local community were pooled over the four survey years from 2016 to 2019. Individual responses were aggregated up to the census tract (CT) level.

    Release date: 2021-11-16
  • 2. Statistics Netherlands and AI Archived
    Articles and reports: 11-522-X202100100011
    Description: The ways in which AI may affect the world of official statistics are manifold and Statistics Netherlands (CBS) is actively exploring how it can use AI within its societal role. The paper describes a number of AI-related areas where CBS is currently active: use of AI for its own statistics production and statistical R&D, the development of a national AI monitor, the support of other government bodies with expertise on fair data and fair algorithms, data sharing under safe and secure conditions, and engaging in AI-related collaborations.

    Key Words: Artificial Intelligence; Official Statistics; Data Sharing; Fair Algorithms; AI monitoring; Collaboration.

    Release date: 2021-11-05
  • 3. Responsible use of machine learning at Statistics Canada Archived
    Articles and reports: 11-522-X202100100002
    Description:

    A framework for the responsible use of machine learning processes has been developed at Statistics Canada. The framework includes guidelines for the responsible use of machine learning and a checklist, which are organized into four themes: respect for people, respect for data, sound methods, and sound application. All four themes work together to ensure the ethical use of both the algorithms and results of machine learning. The framework is anchored in a vision that seeks to create a modern workplace and provide direction and support to those who use machine learning techniques. It applies to all statistical programs and projects conducted by Statistics Canada that use machine learning algorithms. This includes supervised and unsupervised learning algorithms. The framework and associated guidelines will be presented first. The process of reviewing projects that use machine learning, i.e., how the framework is applied to Statistics Canada projects, will then be explained. Finally, future work to improve the framework will be described.

    Keywords: Responsible machine learning, explainability, ethics

    Release date: 2021-10-15
  • 4. Predicting transitions into and out of poverty using machine learning Archived
    Articles and reports: 11-522-X202100100003
    Description:

    The increasing size and richness of digital data allow for modeling more complex relationships and interactions, which is the strongpoint of machine learning. Here we applied gradient boosting to the Dutch system of social statistical datasets to estimate transition probabilities into and out of poverty. Individual estimates are reasonable, but the main advantages of the approach in combination with SHAP and global surrogate models are the simultaneous ranking of hundreds of features by their importance, detailed insight into their relationship with the transition probabilities, and the data-driven identification of subpopulations with relatively high and low transition probabilities. In addition, we decompose the difference in feature importance between general and subpopulation into a frequency and a feature effect. We caution for misinterpretation and discuss future directions.

    Key Words: Classification; Explainability; Gradient boosting; Life event; Risk factors; SHAP decomposition.

    Release date: 2021-10-15
  • 5. International population-based health surveys linked to outcome data: A new resource for public health and epidemiology
    Articles and reports: 82-003-X202000700002
    Description:

    This paper's objectives are to examine the feasibility of pooling linked population health surveys from three countries, facilitate the examination of health behaviours, and present useful information to assist in the planning of international population health surveillance and research studies.

    Release date: 2020-07-29
  • 6. Aboriginal Peoples Survey, 2017: Concepts and Methods Guide Archived
    Articles and reports: 89-653-X2018001
    Description:

    This Concepts and Methods Guide is intended to provide a detailed review of the 2017 APS with respect to its subject matter and methodological approaches. It is designed to assist APS data users by serving as a guide to the concepts and measures of the survey as well as the technical details of the survey's design, field work and data processing. This guide is meant to provide users with helpful information on how to use and interpret survey results. The discussion on data quality also allows users to review the strengths and limitations of the data for their particular needs.

    Chapter 1 of this guide provides an overview of the 2017 APS by introducing the survey's background and objectives. Chapter 2 outlines the survey's themes and explains the key concepts and definitions used for the survey. Chapters 3 to 6 cover important aspects of the APS survey methodology, sampling design, data collection and processing. Chapters 7 and 8 review issues of data quality and caution users about comparing 2017 APS data with data from other sources. Chapter 9 outlines the survey products available to the public, including data tables, analytical articles and reference material. The Appendices provide a comprehensive list of survey indicators, extra coding categories and standard classifications used on the APS. Lastly, a glossary of survey terms is also provided.

    Release date: 2018-11-26
  • 7. Defining retirement Archived
    Articles and reports: 75-001-X200710213182
    Geography: Canada
    Description:

    Even though the retirement wave will have significant labour market consequences over the next 20 years, no regular statistics are produced on retirement or the retired. Part of the problem stems from lack of clear definitions. For some, retirement means complete withdrawal from the labour force while for others it entails part- or even full-time work. The article examines the challenges faced by statistical organizations in measuring retirement and offers several recommendations to inform a discussion for arriving at international standards.

    Release date: 2007-03-20
  • 8. Holistic response management of business surveys Archived
    Articles and reports: 11-522-X20050019440
    Description:

    For a number of years, Statistics Canada has been taking incremental steps to improve its survey programs through the use of tax data substitution, content fine tuning and earlier data releases. The approach is to focus survey collection and analysis on the large, complex enterprises where tax data is insufficient to meet the needs of the Canadian statistical system.

    Release date: 2007-03-02
  • 9. Impact of informativeness of the sample design on statistical inference Archived
    Articles and reports: 11-522-X20050019475
    Description:

    To determine and measure the impact of informativeness we compare design-based and model-based variances of estimated parameters, as well as the estimated parameters themselves, in a logistic model under the assumption that the postulated model is true. An approach for assessing the impact of informativeness is given. In order to address the additional complexity of the impact of informativeness on power, we propose a new approximation for a linear combination of non-central chi-square distributions, using generalized design effects. A large simulation study, based on generating a population under the postulated model, using parameter estimates derived from the NPHS, allows us to detect and to measure the informativeness, and to compare the robustness of studied approaches.

    Release date: 2007-03-02
  • 10. Surveying Aboriginal and Torres Strait islander peoples: Strategies and methodologies of the Australian Bureau of Statistics Archived
    Articles and reports: 11-522-X20040018654
    Description:

    In Australia, cultural considerations influence the statistical activity with regards to Indigenous population. The paper discusses survey designs, operations, estimation and dissemination.

    Release date: 2005-10-27
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Articles and reports (18)

Articles and reports (18) (0 to 10 of 18 results)

  • 1. Measuring Social Capital at the Neighbourhood Level: Experimental Estimates of Sense of Belonging to the Local Community Measured at the Census Tract Level
    Articles and reports: 11-633-X2021007
    Description:

    Statistics Canada continues to use a variety of data sources to provide neighbourhood-level variables across an expanding set of domains, such as sociodemographic characteristics, income, services and amenities, crime, and the environment. Yet, despite these advances, information on the social aspects of neighbourhoods is still unavailable. In this paper, answers to the Canadian Community Health Survey on respondents’ sense of belonging to their local community were pooled over the four survey years from 2016 to 2019. Individual responses were aggregated up to the census tract (CT) level.

    Release date: 2021-11-16
  • 2. Statistics Netherlands and AI Archived
    Articles and reports: 11-522-X202100100011
    Description: The ways in which AI may affect the world of official statistics are manifold and Statistics Netherlands (CBS) is actively exploring how it can use AI within its societal role. The paper describes a number of AI-related areas where CBS is currently active: use of AI for its own statistics production and statistical R&D, the development of a national AI monitor, the support of other government bodies with expertise on fair data and fair algorithms, data sharing under safe and secure conditions, and engaging in AI-related collaborations.

    Key Words: Artificial Intelligence; Official Statistics; Data Sharing; Fair Algorithms; AI monitoring; Collaboration.

    Release date: 2021-11-05
  • 3. Responsible use of machine learning at Statistics Canada Archived
    Articles and reports: 11-522-X202100100002
    Description:

    A framework for the responsible use of machine learning processes has been developed at Statistics Canada. The framework includes guidelines for the responsible use of machine learning and a checklist, which are organized into four themes: respect for people, respect for data, sound methods, and sound application. All four themes work together to ensure the ethical use of both the algorithms and results of machine learning. The framework is anchored in a vision that seeks to create a modern workplace and provide direction and support to those who use machine learning techniques. It applies to all statistical programs and projects conducted by Statistics Canada that use machine learning algorithms. This includes supervised and unsupervised learning algorithms. The framework and associated guidelines will be presented first. The process of reviewing projects that use machine learning, i.e., how the framework is applied to Statistics Canada projects, will then be explained. Finally, future work to improve the framework will be described.

    Keywords: Responsible machine learning, explainability, ethics

    Release date: 2021-10-15
  • 4. Predicting transitions into and out of poverty using machine learning Archived
    Articles and reports: 11-522-X202100100003
    Description:

    The increasing size and richness of digital data allow for modeling more complex relationships and interactions, which is the strongpoint of machine learning. Here we applied gradient boosting to the Dutch system of social statistical datasets to estimate transition probabilities into and out of poverty. Individual estimates are reasonable, but the main advantages of the approach in combination with SHAP and global surrogate models are the simultaneous ranking of hundreds of features by their importance, detailed insight into their relationship with the transition probabilities, and the data-driven identification of subpopulations with relatively high and low transition probabilities. In addition, we decompose the difference in feature importance between general and subpopulation into a frequency and a feature effect. We caution for misinterpretation and discuss future directions.

    Key Words: Classification; Explainability; Gradient boosting; Life event; Risk factors; SHAP decomposition.

    Release date: 2021-10-15
  • 5. International population-based health surveys linked to outcome data: A new resource for public health and epidemiology
    Articles and reports: 82-003-X202000700002
    Description:

    This paper's objectives are to examine the feasibility of pooling linked population health surveys from three countries, facilitate the examination of health behaviours, and present useful information to assist in the planning of international population health surveillance and research studies.

    Release date: 2020-07-29
  • 6. Aboriginal Peoples Survey, 2017: Concepts and Methods Guide Archived
    Articles and reports: 89-653-X2018001
    Description:

    This Concepts and Methods Guide is intended to provide a detailed review of the 2017 APS with respect to its subject matter and methodological approaches. It is designed to assist APS data users by serving as a guide to the concepts and measures of the survey as well as the technical details of the survey's design, field work and data processing. This guide is meant to provide users with helpful information on how to use and interpret survey results. The discussion on data quality also allows users to review the strengths and limitations of the data for their particular needs.

    Chapter 1 of this guide provides an overview of the 2017 APS by introducing the survey's background and objectives. Chapter 2 outlines the survey's themes and explains the key concepts and definitions used for the survey. Chapters 3 to 6 cover important aspects of the APS survey methodology, sampling design, data collection and processing. Chapters 7 and 8 review issues of data quality and caution users about comparing 2017 APS data with data from other sources. Chapter 9 outlines the survey products available to the public, including data tables, analytical articles and reference material. The Appendices provide a comprehensive list of survey indicators, extra coding categories and standard classifications used on the APS. Lastly, a glossary of survey terms is also provided.

    Release date: 2018-11-26
  • 7. Defining retirement Archived
    Articles and reports: 75-001-X200710213182
    Geography: Canada
    Description:

    Even though the retirement wave will have significant labour market consequences over the next 20 years, no regular statistics are produced on retirement or the retired. Part of the problem stems from lack of clear definitions. For some, retirement means complete withdrawal from the labour force while for others it entails part- or even full-time work. The article examines the challenges faced by statistical organizations in measuring retirement and offers several recommendations to inform a discussion for arriving at international standards.

    Release date: 2007-03-20
  • 8. Holistic response management of business surveys Archived
    Articles and reports: 11-522-X20050019440
    Description:

    For a number of years, Statistics Canada has been taking incremental steps to improve its survey programs through the use of tax data substitution, content fine tuning and earlier data releases. The approach is to focus survey collection and analysis on the large, complex enterprises where tax data is insufficient to meet the needs of the Canadian statistical system.

    Release date: 2007-03-02
  • 9. Impact of informativeness of the sample design on statistical inference Archived
    Articles and reports: 11-522-X20050019475
    Description:

    To determine and measure the impact of informativeness we compare design-based and model-based variances of estimated parameters, as well as the estimated parameters themselves, in a logistic model under the assumption that the postulated model is true. An approach for assessing the impact of informativeness is given. In order to address the additional complexity of the impact of informativeness on power, we propose a new approximation for a linear combination of non-central chi-square distributions, using generalized design effects. A large simulation study, based on generating a population under the postulated model, using parameter estimates derived from the NPHS, allows us to detect and to measure the informativeness, and to compare the robustness of studied approaches.

    Release date: 2007-03-02
  • 10. Surveying Aboriginal and Torres Strait islander peoples: Strategies and methodologies of the Australian Bureau of Statistics Archived
    Articles and reports: 11-522-X20040018654
    Description:

    In Australia, cultural considerations influence the statistical activity with regards to Indigenous population. The paper discusses survey designs, operations, estimation and dissemination.

    Release date: 2005-10-27
Journals and periodicals (0)

Journals and periodicals (0) (0 results)

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