Retail Trade Survey (Monthly): CVs for total sales by geography - June 2022

CVs for Total sales by geography
This table displays the results of Retail Trade Survey (monthly): CVs for total sales by geography – June 2022. The information is grouped by Geography (appearing as row headers), Month and Percent (appearing as column headers)
Geography Month
202206
%
Canada 0.6
Newfoundland and Labrador 1.9
Prince Edward Island 1.0
Nova Scotia 1.8
New Brunswick 1.9
Quebec 1.2
Ontario 1.2
Manitoba 1.1
Saskatchewan 3.4
Alberta 1.2
British Columbia 1.7
Yukon Territory 1.9
Northwest Territories 2.0
Nunavut 1.3

Application Program Interface (API)

Web services are commonly referred to as an API (Application Programmer Interface). The API allows data users to access Statistics Canada aggregate data and metadata by connecting directly to our public facing databases.

The Web Data Service is an API service that will provide access to data and metadata released by Statistics Canada each business day. Web Data Service methods are the preferred mechanism for data users to consume a discrete amount of data points via the Statistics Canada website. This web service provides an access to the main Statistics Canada output database via a number of calls or methods that harvest the data and metadata in their raw forms and return them to the caller. There are two services for our main database: one returns data points in JavaScript Object Notation (JSON) language and the other returns Statistical Data and Metadata Exchange (SDMX) XML output. There are user guides for both our developer pages on the website as well as other reference APIs for other subjects.

For example the JSON API includes the following methods:

  • Product Change Listings
    • getChangedSeriesList
    • getChangedCubeList
  • Cube Metadata and Series Information:
    • getCubeMetadata
    • getSeriesInfoFromCubePidCoord
    • getSeriesInfoFromVector
  • Data Access; data changes for today, over time and full table
    • getChangedSeriesDataFromCubePidCoord
    • getChangedSeriesDataFromVector
    • getDataFromCubePidCoordAndLatestNPeriods
    • getDataFromVectorsAndLatestNPeriods
    • getBulkVectorDataByRange
    • getDataFromVectorByReferencePeriodRange
    • getFullTableDownloadCSV
    • getFullTableDownloadSDMX
  • Supplemental Information
    • getCodeSets

Please see the Web Data Service (WDS) user guide and documentation for more information.

Date modified:

Statistical Geomatics Centre seeking input on Census Geography's products and services

Opened: July 2022
Closed: October 2022

Consultative engagement objectives

The Statistical Geomatics Centre and the Consultative Engagement Team are working together to improve the Census Geography's line of products and services.

Geography is central to the dissemination of Census-related information, and we would like you to share your experience with us to ensure that our users can leverage and use our substantial library of products and services to their full extent.

Your feedback will have a direct impact on informing the development of better geographical products. We believe that this project will be mutually beneficial to Statistics Canada and its users: catering to your needs ensures that we innovate and stay 'ahead of the curve' in this dynamic geographic ecosystem.

How to get involved

This consultation is now closed.

Individuals who wish to obtain more information on this engagement initiative may contact us by email at statcan.statcanengage-statcanmobilise.statcan@statcan.gc.ca.

Statistics Canada is committed to respecting the privacy of participants. All personal information created, held or collected by the agency is protected by the Privacy Act. For more information on Statistics Canada's privacy policies, please consult the privacy notice.

Results

Summary results of the engagement initiatives will be published online when available.

Date modified:

In August 2022, questions measuring the Labour Market Indicators were added to the Labour Force Survey as a supplement.

Question wording within the collection application is controlled dynamically based on responses provided throughout the survey.

Labour Market Indicators

ENTRY_Q01 / EQ1 - From the following list, please select the household member that will be completing this questionnaire on behalf of the entire household.

WFH_Q01 / EQ2 - At the present time, in which of the following locations (do/does) (Respondent's name/this person/you) usually work as part of (his/her/their/your) main job or business?

WFH_Q02 / EQ3 - Last week, what proportion of (his/her/their/your) work hours did (Respondent name/this person/you) work at home as part of (his/her/their/your) main job or business?

VAL_Q01 / EQ4 – In general, how important are each of the following to (Respondent's name/this person/you) in the workplace?

VAL_Q02 / EQ5 – Does (Respondent's name's/this person's/your) main job or business align with what (he/she/they/you) value(s) in the workplace?

VAL_Q03 / EQ6 – How important is it to (Respondent's name/this person/you) that (his/her/their/your) job or business align with what (he/she/they/you) value(s) in the workplace?

ETH_Q01 / EQ7 – To what extent do you agree or disagree with the following statement: If financial stability was guaranteed, (Respondent's name/this person/you) would be happier if (he/she/they/you) never had to work again.

ETH_Q02 / EQ8 – Usually, (do/does) (Respondent's name/this person/they/you) look forward to the end of the work day?

LEA_Q01 / EQ9 – In the next 12 months, (are/is) (Respondent's name/this person/you) planning on leaving (his/her/their/your) main job or business?

LEA_Q02 / EQ10 – What is the main reason why (Respondent's name/this person/you) (is/are) planning on leaving (his/her/their/your) main job or business?

Report and Draft Recommendations: Engagement on Corrections Disaggregated Data and Analysis Strategy

Report and Draft Recommendations: Engagement on Corrections Disaggregated Data and Analysis Strategy (PDF, 866 KB)

Canadian Centre for Justice and Community Safety Statistics (CCJCSS)

Table of Contents

Executive Summary

Over the years, there have been increasing demands for better disaggregated data to shed light on people's diverse experiences with the police and the justice system. Disaggregated data can help to identify and respond to issues of social inequities, discrimination, and systemic racism within Canadian society. Concerns for the disparate treatment of Indigenous and racialized peoples in the Canadian criminal justice system revealed important gaps in the availability of disaggregated data. This situation is especially true for information on the identity of people who encounter police for various reasons, including criminal incidents.

In response to these growing demands, Statistics Canada is in the process of developing a Corrections Disaggregated Data and Analysis Strategy on the Representation of Indigenous and Racialized Groups in Canada's Correctional Systems. This strategy aims to better understand the experiences of Indigenous and racialized groups in terms of their interactions and involvement with correctional systems and with the criminal justice system more generally. Prior to starting development of the strategy, the Canadian Centre for Justice and Community Safety Statistics (CCJCSS) engaged numerous partners of interest, including Indigenous and racialized community groups and organizations, and sought input through the Engagement on Corrections Representation Data & Analysis Strategy. This report provides the background and key results of the Engagement, including seven key recommendations.

Recommendation 1
Statistics Canada should develop population-based indicators and re-contact indicators using disaggregated data to measure representation of sub-populations in correctional systems;

Recommendation 2
Statistics Canada should disaggregate its correctional services data as much as possible;

Recommendation 3
Relationships between socio-economic and mental health issues and over-representation should be analyzed further;

Recommendation 4
Statistics Canada should engage in data quality evaluations of the disaggregated data information collected;

Recommendation 5
Statistics Canada should include appropriate context as part of the data analysis process, and work closely with affected populations when publishing disaggregated data;

Recommendation 6
Statistics Canada should review options for dissemination to enhance data accessibility and use; and

Recommendation 7
Statistics Canada should regularly review its definitions, terminology and categorizations in order to ensure that the language used is appropriate and culturally-sensitive.

Background

Through CCJCSS, Statistics Canada has a long history of publishing data on Indigenous persons in corrections. Most of the reporting to date has focused on presenting the number of admissions (with breakdowns by custody/community and adult/youth) for a given fiscal year by Indigenous identity. Data on Indigenous identity by admission is available back to 1997/1998 for youth and 2000/2001 for adult corrections.

The CCJCSS is currently in the process of developing a Corrections Disaggregated Data and Analysis Strategy: Representation of Indigenous and Racialized Groups in Canada's Correctional Systems (for ease of reference, referred to hereafter as: The Corrections Representation Data & Analysis Strategy).

The Engagement on Corrections Representation Data & Analysis Strategy sought input from partners and data users outside of Statistics Canada to guide the development of its statistical program. Our goal is to provide our partner organizations and the public at large with up-to-date disaggregated data and information pertaining to correctional services in Canada. The Engagementinvolved respondents from a wide and diverse range of perspectives, including: Indigenous and racialized groups and organizations; corrections agencies; academics; and other interested parties at the national and provincial/territorial government levels. Feedback was sought on the following:

  • Current key indicators produced by Statistics Canada related to Indigenous peoples' over-representation in corrections, and ways in which the indicators and analysis can be improved to be more relevant to data users and the public;
  • In addition to the historical focus at Statistics Canada on Indigenous peoples' involvement in correctional systems, explore the importance of expanding the national corrections statistical program to collect, analyze and produce indicators that provide relevant and timely information for Black, Hispanic, South Asian, East and Southeast Asian and other racialized groups;
  • Important contextual information to consider and present when disseminating disaggregated data; and
  • Assessments of data quality.

Feedback was obtained in two ways: (1) from written responses to an engagement document; and (2) from participation in small-group discussions led by Statistics Canada.

Methods

Engagement Document

The written engagement document, both in French and English, was sent to 322 partners and community organizations on November 6, 2021. The original deadline was extended from November 26, 2021 to December 24, 2021. As of December 31, 2021, 33 responses were received and analyzed. Respondents were asked to answer 16 questions in the written document which consisted of a combination of yes/no questions, Likert scales, and open-ended questions.

Small Group Discussions

Due to the impact of the on-going COVID-19 pandemic, small group discussions were held virtually between November and December 2021. Small group discussions for the Canadian Correctional Statistics Survey (CCSS) were conducted in tandem with the Uniform Crime Reporting Survey (UCR) for a total of 41 participants. There were 25 participants who joined the CCSS-specific small group discussions; they were invited to attend a session based on their organization affiliation:

  • Indigenous groups and organizations;
  • Racialized groups and organizations;
  • Correctional services agencies;
  • Academics; and
  • Other interested parties at the national and provincial/territorial government levels.

The discussions were held in both French and English, and were facilitated by a neutral, third-party moderator from Statistics Canada's Internal Engagement team. For each session, the moderator posed the same 12 questions in the same order. These questions were derived directly from the written engagement document and were shortened to be more 'interview-friendly'. Moreover, the moderator encouraged further discussion among the participants and at times would offer prompts such as "How do you see this being useful?" to help move the conversation along and to gain more insight into a particular answer.

Response Rates

Engagement Document

Thirty-three (33) written document responses were received for an overall response rate of 10.3%. The breakdown was as follows:

  • Federal Partners / Stakeholders: 33.3%
  • Criminal Justice: 27.3%
  • Correctional Services Programs: 15.2%
  • Ethno-Cultural Groups / Organizations: 6.1%
  • Indigenous Representative Bodies: 6.1%
  • Other Partners / Stakeholders: 12.2%

Please note that the total sum of the individual percentages above does not add up to 100.0% due to rounding.

The low total response rate can be attributed, at least in part, to response and respondent burden. For instance, some respondents had indicated that they found the engagement document too long and parts of it too complex.

In the coming months, there will be additional opportunities for comments and engagement with partners and stakeholders as Statistics Canada, through CCJCSS, develops its five-year Corrections Representation Data & Analysis Strategy.

Small Group Discussions

Of the 25 individuals participating in the CCSS-specific virtual small group discussions, the majority (32.0%) represented organizations from the Federal Partners / Stakeholders category.

Recommendations

Recommendation 1

Statistics Canada should develop population-based indicators and re-contact indicators using disaggregated data to measure representation of sub-populations in correctional systems

Current Measures of Over-Representation

Recent studies and reports, as well as those going back decades, have highlighted and drawn attention to how the experiences of First Nations peoples, Métis and Inuit and other racialized groups and populations in the Canadian criminal justice system have been marked by over-representation and inequitable treatment. First Nations peoples, Métis and Inuit, for instance, have long and unique social, cultural and political histories in Canada. Most notably, the history of colonialism – including residential schools and culturally insensitive and inaccessible programs – and settler colonial policies continue to seriously impact Indigenous people and communities to this day. As a result, Indigenous peoples have experienced and continue to experience social, economic and institutional marginalization, and also various forms of inter-generational trauma.

Statistics Canada currently measures over-representation by proportion of admissions, where the individual self-identifies as Indigenous. Admissions are counted each time a person begins any new legal status while being supervised in a correctional institution. This means that the same person may be included several times in the admission counts where they move from one correctional program to another (e.g., person initially enters corrections on a remand status then to sentenced custody later in the same involvement – this scenario would count as two admissions, one for remand and one for sentenced custody) or re-enter the system later in the same year. Admissions therefore represent the number of all entries during a fiscal year to each type of legal status (remand, sentenced custody or a community supervision program), and track correctional events more than persons supervised by the system.

Proposed New Indicators

Population-based Measures (Incarceration Rates and Custodial Involvement Rates)

Statistics Canada is exploring developing population-based measures that would present involvement in the correctional system as a rate or percentage of the overall target population as our main indicator of representation. Population-based measures present involvement in the correctional system as a rate or percentage of the overall target population as the main indicator of representation. This includes taking into account incarceration rate and custodial involvement rate indicators.

Incarceration rate measures the proportion of a population in custody on an average day in the year. It is calculated by taking the Average Daily Count (ADC) of the correctional population then dividing it by the general population estimate for that same year. For the CCSS, the rate is expressed as the number of incarcerated persons per 10,000 population. For example, a rate of 100 for Canada means that, on an average day in the year, 1% of the population in Canada was incarcerated. With the CCSS, ADC is now available by Indigenous and racialized groups, allowing Statistics Canada to produce both Indigenous and Non-Indigenous incarceration rate for the population as a whole, or apply intersectionality to the rates (e.g., limit to adult males, adult females, youth between the ages of 12 to 17, etc.). Over-representation (for Indigenous persons for example) would be measured by the relative difference between the Indigenous and Non-Indigenous Incarceration Rates.

Custodial involvement rate measures the proportion of a specific populations experiencing custody over a reference period. The measure identifies the number of unique persons spending at least one day in custody during the reference period for a defined population (Indigenous, Black, young males, etc.), then calculates the percentage of the population experiencing incarceration. Individuals are counted equally, whether or not they spent one night in custody or the whole year.

Over-Representation Index (of Indigenous Populations)

Studies have shown that being young and male are risk factors for involvement in crime. The Over-representation Index would account for differences in age and sex profile of different populations when calculating rates of incarceration. The Over-representation Index recalculates the relative difference between Indigenous and non-Indigenous rates, as if both populations have an age/sex profile identical to the national population distribution. For instance, for a province or territory where the Indigenous population is younger or proportionally more male, there could be a lower score on the Over-representation Index than the actual relative differences between the Indigenous and non-Indigenous Incarceration Rates. Likewise, over time, as population profiles change for a province or territory, the Over-representation Index controls for these changes, reducing the impact demographic shifts may have on the over-representation measurement.

While our initial work on the Over-representation Index has been limited to measuring Over-representation in Indigenous populations, the concepts developed can be applied to other populations, such as Black people in Canada, as well as applying intersectionality.

Re-contact Indicator

Re-contact refers to a measure of return to the justice system after initial release. The re-contact indicator is complicated, with a number of different elements: (1) The reference event is the starting point from which re-contact for an individual is assessed (i.e. when the "clock" starts); (2) Follow-up period: Length of time over which an offender is observed (e.g. 2 years from reference event); (3) Re-contact Event: The re-contact event is defined as the occurrence and start date of any new legal hold status occurring after the reference event and within the follow-up period. There are three metrics associated with the definition of re-contact, listed below:

  • Prevalence (size of the issue): number/proportion of offenders with a re-contact event within the follow-up period?
  • Frequency (how active): how many re-contacts did individuals have during the follow up period (e.g., are most re-contacts due to a small group with a large number of recontacts?)
  • Elapsed time (time to re-contact): how much time passed between the reference event and a re-contact event?

Statistics Canada is currently working with Public Safety on the Pan-Canadian Re-contact Strategy. The strategy aims to continue work on the re-contact indicators, with an initial focus on persons re-contacting the justice system after going through corrections. Statistics Canada is currently reviewing the re-contact definitions and is evaluating adding an escalation metric (indicator of whether the severity of offences associated with re-contacts are increasing or decreasing).

What we heard

Current Measures

Four in ten (42%) of the written document respondents and 52% of the small group discussion participants indicated that observing the rate of admission is useful for measuring the over-representation of incarcerated Indigenous and racialized groups. However, there are concerns surrounding how this method can lead to multiple counts of one individual and therefore, can impact the accuracy and quality of the data. As such, an alternative method was suggested by the majority of respondents: measure over-representation via daily count to avoid the risk of double-counts of re-admission. This would also paint a more accurate picture of the situation inside the correctional facilities.

There is a strong consensus among the Engagement participants that there is an immediate need to develop an official definition for over-representation, and to also implement a national, standardized Over-Representation Index to be used across all correctional systems.

Population-based Measures

Seven in ten (70%) of the written document respondents and 80% of the small group discussion participants have indicated that developing population-based measures would be useful to meet their data needs. There is an overall consensus among all the participants in the Engagement project that population-based measures would help advance our knowledge because it would allow researchers to draw comparisons across provinces and territories. Moreover, this measure would be beneficial to design culturally appropriate programs and to engage with communities in a meaningful way.

Over-Representation Index

Eight in ten (82%) of the written document respondents and 84% of the small group discussion participants have indicated that, in general, the Over-Representation Index would be a very useful measure. More specifically, 70% of the written document respondents also indicated that it would be especially useful to present a national indicator of over-representation by integrating CSC (Correctional Service of Canada) and Provincial/Territorial results (see Figure 1 below).

Percent of written document respondents who found population-based indicators useful for measuring and analyzing over-representation of vulnerable populations
Description for Figure 1: Percentage of respondents finding indicator very useful for measuring and analysing over-representation of vulnerable populations
Percentage of respondents finding indicator very useful for measuring and analysing over-representation of vulnerable populations
  Percentage (%)
Proportion of admissions 48.48
Population/rate based indicators 72.72
Over-representation index 87.88
Recontact indicators 90.91

Re-contact Indicators

Almost nine in ten (88%) of the written document respondents agree that it would be useful to them and their organization to enhance current re-contact indicators. This would include an initial emphasis on correctional data by identifying criminal justice system re-contacts after release from correctional services. The strategy would produce rates of re-contact for the overall correctional population and disaggregate into groups. Similarly, 84% of the small group discussion participants agree that disaggregating rates of re-contact for the overall population would be useful. Furthermore, 32% of the participants have suggested that greater level of detail needs to be included within the re-contact indictor, such as reason for re-contact, quantity of re-contacts, length of stay, and type of offence.

Measures of Over-Representation Used by STC (Statistics Canada) Partners

Almost nine in then (89%) of the written document respondents have indicated that their organization collects and analyzes data on over-representation. 56% of the small group discussion participants collect their own data on over-representation while 44% of participants work with the data collected by Statistics Canada. Furthermore, the majority of participants from both the written document (66%) and the small group discussions (68%) have indicated that they do not have an official, standardized method of measuring and evaluating over-representation. Four in ten (42%) of the written document respondents and 40% of the small group discussion participants measure over-representation by comparing the proportion of the Canadian population to the number of incarcerated individuals. On the other hand, some respondents have indicated that they do have a method of measuring over-representation through the use of several indicators, such as through admission rate, observing the proportion of Indigenous and racialized prisoners, evaluating proportion of dangerous prisoners, and understanding mental health needs.

Recommendation 2

Statistics Canada should disaggregate its correctional services data as much as possible

Overall consensus
The present data on racialized identity is too general and does not accurately represent the cultural diversity that exists within Indigenous peoples and racialized groups

In addition to understanding the incarceration experiences of Indigenous people, Statistics Canada seeks to expand its program to also collect and analyze racialized identity. Respondents were asked several questions on the collection, assessment, and presentation of corrections data for Indigenous and racialized groups. The responses varied when respondents addressed issues facing racialized groups and Indigenous peoples.

Results drawn from current data cannot be used to draw conclusions about the larger population and should only be strictly applied to those in the dataset. Therefore, Statistics Canada needs to develop a strategy to disaggregate the data as much as possible so that the correctional population can be accurately represented.

Disaggregated data for Racialized groups

The findings from the Engagement suggest that there is a strong need to disaggregate race data as much as possible. Racialize identity and ethnicity are often conflated with one another, but they are separate. "Race" is a social construct and does not have any biological basis; it is ascribed to individuals based on their physical characteristics (e.g., skin colour). Ethnicity, on the other hand, encompasses everything from language, to nationality, to religion, and culture. As such, an individual can have multiple/mixed racial identities and ethnicities.

Fifty-two (52%) of the written document respondents indicate race data should be disseminated to include ethnic origin and allow for multiracial identities. It is harmful to collapse identities in one category, as individuals have very different experiences depending on their racial and ethnic identity and should be avoided where possible. Respondents also underscored that it is crucial to allow for the reporting of multiple/mixed racial identities, and it is equally important that such data is disaggregated appropriately. However, no feedback was offered on approaches to analyze and disseminate multi-racial categories, therefore the ideal approach CCJCSS should take regarding this will require further exploration and engagement.

Overall, the respondents would like to see a clear distinction made between race-based data and ethnicity data. Just as how the historical and cultural diversity among Indigenous people is recognized, the same is recommended for racialized groups. For example, "Black" is race-based data because it is socially constructed. However, it does not accurately portray the cultural diversity that exists among Black communities. The experiences of individuals who descend from African-Americans fleeing slavery from the United States is very different than recent immigrants from North Africa or the Caribbean. As such, collecting ethnic-based data would allow for a more accurate portrayal of the incarcerated population, rather than just grouping everyone under the same label as their racialized identity.

Indigenous Groups and Peoples

A frequent misconception is the idea that Indigenous people are homogenous. Thirty percent (30%) of the written document respondents and 16% of the small group discussion participants recognize the diversity and heterogeneity of Indigenous groups and peoples. They agree there is a need to disaggregate the correctional data as much as possible otherwise it becomes difficult to determine the extent to which the aggregated data among Indigenous populations can be generalized to each sub-group. Furthermore, respondents indicated that it would be helpful to examine the differences and similarities between First Nations, Inuit, and Métis people to better understand their experiences with the correctional system and to develop culturally appropriate programs. There is also a need to understand the major regional variation regarding the over-representation of Indigenous people. 18% of the written document respondents and 16% of the small group discussion participants have indicated that the data should be disaggregated by geographical location, such as those living on- or off-reserve. Moreover, 12% of the written document respondents stressed that the data should also be disseminated by regional differences, such as urban or rural dwellings.

Recommendation 3

Statistics Canada should further analyze the relationship between socio-economic and mental health issues and the over-representation of certain groups in correctional systems

Overall consensus
Additional socio-economic and mental health factors should be considered by Statistics Canada when conducting analysis of over-representation

Respondents were specifically asked to identify important contextual information and factors that Statistics Canada should consider when presenting data and writing analytical reports pertaining to Indigenous, racialized and other diverse populations. Understanding additional contextual factors that may contribute to over-representation will ultimately allow for the development of evidence-based approaches to appropriately respond to the phenomenon.

Responses to both the written engagement exercise and small group discussions indicated a rich variety of additional socio-economic and mental health factors that should be considered by Statistics Canada when conducting analysis of over-representation. Some factors were more frequently identified than others (such as education), but the majority of respondents were very clear in asserting that over-representation data cannot be analyzed solely on its own accord. As one respondent explained, "We cannot consider over-representation data in isolation of other data sets such as health and education data."

Additional socio-economic and mental health factors

Respondents to the written engagement noted many socio-economic factors and mental health issues that are associated with over-representation. Education was the area respondents most frequently noted, with 91% indicating that education needs to be considered when conducting data analysis on over-representation. The next factors most frequently noted by respondents were mental health, labour force, and age and gender, with 85% of respondents observing that these areas need to be considered. Other areas to be considered in data analysis on over-representation are noted in Figure 2 below:

Top 10 areas to be considered when doing data analysis on over-representation
Description for Figure 2: Top 10 areas to be considered when doing data analysis on overrepresentation
Top 10 areas to be considered when doing data analysis on overrepresentation
  Percentange (%)
Breach 54.54545
Community Supervision 60.60606
Risk/Need 69.69697
Gang 72.72727
Offences 75.75758
Marginalization 81.81818
Age & Gender 84.84848
Labour Force 84.84848
Mental Health 84.84848
Education 90.90909

Respondents to the written engagement also noted substance use, marital/family stability, housing, sexual orientation, programming availability, length of incarceration, intergenerational trauma, and childhood maltreatment as other factors impacting over-representation.

The small group discussions further identified many factors impacting over-representation, such as homelessness (16%), mental health (16%), experience of violence and/or sexual violence (12%), housing (8%), state of crisis/emergency (8%), cost of living (8%), substance use (8%), and immigration status (8%).

Going forward, it will be very important for Statistics Canada to consider data on over-representation within the context of social issues. The aforementioned factors identified by respondents will guide the focus of Statistics Canada in conducting future analyses of over-representation data, with particular emphasis on those factors that were most frequently identified.

As one respondent commented, "it is important to ensure that over-representation is contextualized with an understanding of the 'social determinants' of interaction with the criminal justice system." Ultimately, as another respondent noted, "understanding the intersection among health, education, poverty, age, gender, etc. and crime informs broader evidence-driven solutions to understanding crime prevention and successful community integration."

Recommendation 4

Statistics Canada should conduct data quality evaluations of the disaggregated information collected

Overall consensus

  • Current method of collecting self-reporting identity is concerning and can inflict or deepen existing trauma, which can impact the quality of the data
  • Trauma-informed data collection methods may help to mitigate the risk of re-traumatization

The following findings were derived from an open-ended question which asked respondents to indicate any concerns they may have about the quality of data and information collected by correctional programs and other sectors of the criminal justice system in regard to Indigenous people and racialized groups. Overall, the majority of Engagement respondents (85% of the written respondents and 64% of the small group discussion participants) expressed concern about the quality of disaggregated data collected by correctional services and other sections of the justice system regarding Indigenous peoples.

The strongest concern that was discussed by the Engagement participants (15% of the written document participants and 12% of the small group discussion participants) revolve around data quality regarding identity. 40% of the written document respondents are concerned about Indigenous identity and 48% of respondents indicated that the current measures of self-reporting identity is problematic. Participants indicated that Indigenous individuals are often more hesitant to disclose their Indigenous identity at intake, for various reasons. Indigenous individuals may feel that declaring their identity will invite further discrimination within the correctional facility from both prison workers and prisoners, especially if the prison worker in question is White. Moreover, 12% of the small group discussion participants are concerned with the lack of consent surrounding identity collection, and 10% are concerned with the potential for re-traumatization due to data collection. Furthermore, 15% of the small group discussion participants have identified that there could be privacy implications among small cohort sizes. It may be easier to identify the individual in question if the admissions of a particular group is small.

In terms of the data collection methods, 30% of the written documents respondents are concerned with how Indigenous identity data is collected. More specifically, 6% of the written document respondents and 12% of the small group discussion participants are concerned that the data collection officer does not have any culturally appropriate training, and may create further trauma for Indigenous peoples at intake. 6% of the written documents respondents have suggested that trauma-informed data collection methods may help to mitigate the risk of re-traumatization. In addition, 36% of the small group discussion participants problematized the lack of standardized identity categories and 29% participants noted the lack of identity categories for Indigenous people, which contributes significantly to the rates of misidentification.

Recommendation 5

Statistics Canada should include appropriate context as part of the data analysis process, and work closely with affected populations when publishing disaggregated data

Overall consensus

  • The historical and social context for marginalized groups needs to be strongly articulated and acknowledged to avoid perpetuating stereotypes
  • Statistics Canada needs to consult and collaborate with marginalized communities in research methods development
  • Racial identity and ethnicity need to be understood and operationalized as separate variables

A key concern noted by respondents was the possibility of adverse impacts on vulnerable populations resulting from Statistics Canada publications of representation and disaggregated data. The majority of respondents (64% from the written engagement raised this concern) noted the importance of ensuring over-representation is understood as a systems-based problem.

Respondents also highlighted the risk of reinforcing stereotypes and racial biases. A further 39% of respondents emphasized the importance of consulting with marginalized communities, and including their voices in the data collection and analysis processes.

Indigenous populations

Discussion group participants echoed the concerns of the written engagement, with many commenting on the need for community-based approaches with Indigenous populations. When working with Indigenous populations, respondents noted that it will be necessary for Statistics Canada to acknowledge historical injustices, the impact of colonialism, and recognizing that Indigenous peoples are not a single, homogenous group.

Many discussion group participants also commented on the need to provide historical and colonial context, traumas, and systemic racism when presenting the data. Thirty-six percent of both the written document respondents and small group participants agree that the histories and present dynamics of systemic racism should be taken into account when dealing with race-based data. Approximately three out of ten respondents (27%) of the written document respondents are concerned with how systemic discrimination against certain groups and communities have impacted the collection and quality of corrections data. Due to the plurality of histories and experiences of Black and other racialized groups, the data should be collected and presented in a culturally appropriate manner. Similarly, 28% of the small group discussion participants suggested that providing additional socio-economic context and highlighting the differences among racialized and ethnic communities would be beneficial.

Going forward, it will be crucial for Statistics Canada and CCJCSS to work with and engage proactively with Indigenous communities to achieve progress in responding to this recommendation. This could be completed through community engagement exercises such as town halls, as well as by collaborating with Indigenous communities and considering the incorporation of Indigenous research methods that promote Indigenous values and knowledge. A statement from one of the respondents who quoted an Indigenous professor illustrates the importance of doing so:

"We have a very long history in this country of being studied and researched and having data collected on us, only to twist that around to blame the victim in a sense. If you want to collect that data, then you do it with us. And you do it for us."

Racialized groups

In the case of racialized groups, respondents noted that Statistics Canada should refrain from conflating racialized identity and ethnicity.

It was noted that racial and ethnic groups are social constructs, and consequently, factors that lead to the over-representation of certain groups are socially-based (e.g. systemic racism), and not due to any perceived differences on the basis of genetic factors.

Further to this, it was noted that the purpose of the data for these populations is very important in determining how it will be used in the future:

"If the intent is to monitor and address inequalities stemming from racism or systemic bias, then race-based data should be collected and disaggregated. However if the intent is to tailor services or interventions in the community to reduce the overrepresentation of certain groups in correctional settings, then ethnicity-based data should be collected and disaggregated so that language, cultural or religious needs of individuals can be better anticipated. If both these purposes are relevant, than both race and ethnicity data should be collected and disaggregated."

Finally, respondents underscored the need for Statistics Canada to recognize that the experiences and needs of individuals vary significantly due to their racial and cultural histories. As one respondent explained, the histories and current dynamics of systemic racism, the plurality of histories and experiences of racialized groups, as well as other factors contributing to challenges in accessing services and supports need to be considered when Statistics publishes disaggregated data.

Recommendation 6

Statistics Canada should review options for dissemination to enhance data accessibility and use

Overall consensus

  • Publication of a specialized Juristat on over-representation would help deepen current understanding of over-representation
  • Accessing micro-data would help researchers in their research endeavours
  • Introducing additional analytical products that allow for a clearer visual representation of the data

Special topic Juristat reports

Specific to this recommendation, 30% of respondents from the written engagement exercise highlighted that a special topic published in Juristat would allow for a greater understanding of the variables that cause over-representation, as well as access to a direct comparison of findings that provide a more transparent view of how Indigenous and racialized groups are represented. As one respondent commented, "…special topics Juristats are helpful and focusing on characteristics of a specific population for a report can be informative."

Accessibility of micro-data

An additional 12% of respondents from the written engagement exercise proposed that increased accessibility to micro-data will allow researchers to examine a number of questions that will contribute to the advancement of knowledge on over-representation. As one respondent mentioned: "…having this data available as microdata in the Research Data Centres will allow for examination of some of the precursors to over-representation via integrated data projects.

Additional products

Search parameters were also suggested by 9% of respondents from the written engagement exercise. Allowing individuals to help filter data by jurisdiction, types of offence, racialized identity, and other parameters would make it more accessible to users.

Another 6% of respondents suggested that the inclusion of data tables and infographics will allow for a clearer visual representation of the data.

Finally, some respondents from the discussion groups suggested communicating data using familiar platforms, organizations, and resources. For instance, the Aboriginal Peoples Television Network (APTN) was suggested as a platform that could be used to share data.

Recommendation 7

Statistics Canada should regularly review its definitions, terminology and categorizations in order to ensure that the language used is appropriate and culturally-sensitive

Overall consensus

  • Several terminologies need to be replaced and/or redefined
  • Current uses of the words 'over-representation', 'offender', and 'gang affiliation' can be harmful and stigmatizing

Respondents highlighted the need for Statistics Canada to thoughtfully consider its terminology. As one respondent explained:

"The language and terminology used in collection practices, and the framework used to analyze data, should be determined in collaboration with communities that would be impacted by the data…The terms and language should then be shared widely through robust training."

Respondents most often referred to 'over-representation', 'offender', and 'gang affiliation' as terminology that should be reviewed by CCJCSS.

Defining 'over-representation'

The majority of discussion group respondents (56%) stressed the need for an official definition of over-representation, or a standard means by which it can be measured. Academics recommended using the term disproportionate in place of over-represented when commenting on imprisonment data.

Use of 'offender' and 'gang affiliation'

Respondents pointed to the term 'offender' as something that categorizes someone within the correctional system as an 'other'. Categorizing someone as an 'other' minimizes persons to a single characteristic, namely that they are housed within a correctional facility. Further to this, it is an inaccurate descriptor given that people held on remand may be later deemed innocent of their offence.

CCJCSS was also asked to exercise caution with use of the term 'gang affiliation'. This term has been disproportionately applied to Indigenous and racialized groups in the past, and has been applied to individuals who may have associated with individuals in gangs for however brief a period. The label can also be assigned to someone in a correctional facility without the requirement of police or court documentation. Once an individual in a correctional facility is assigned this label, removing it or correcting is "extremely difficult".

Next Steps

Based on these seven recommendations, Statistics Canada, through its CCJCSS, will develop a strategic five-year plan for developing its disaggregated data program with correctional services data. The plan will be comprehensive, addressing survey development, respondent and partner relations, analytical plans, indicator development and data quality evaluations, along with other components of its statistical program.

In the short-term, for fiscal year 2022/2023, CCJCSS will produce a special topic Juristat on Indigenous representation in adult custody (for provinces reporting to CCSS), and include a table on visible minority admissions on its website as part of its annual analysis. Within this context, it is important to note that CCJCSS has not yet developed standards for categorizing racialized groups as it awaits guidance from Statistics Canada on new classifications pertaining to racialized identity and ethnicity.

Date modified:

Supplement to Statistics Canada's Generic Privacy Impact Assessment related to the Survey of Advanced Technology and the Survey of Innovation and Business Strategy

Date: July 2022

Program manager: Director, Investment Science and Technology Division (ISTD)
Director General, Economy-wide Statistics

Reference to Personal Information Bank (PIB)

In accordance with the Privacy Act, Statistics Canada is submitting a new institutional personal information bank (PIB) to describe any personal information about businesses' primary decision makers collected voluntarily at the end of mandatory business surveys for the purposes of the Statistics Act, such as the Survey of Advanced Technology (SAT) and the Survey of Innovation and Business Strategy (SIBS). The following PIB is proposed for review and registration.

Sociodemographic Information on Business Primary Decision Makers

Description: This bank describes personal information that relates to business' primary decision makers collected voluntarily at the end of mandatory business surveys. Personal information may include gender, sexual and gender diversity, Indigenous Peoples, visible minority, persons with a disability, citizenship and immigration status, education and age group.

Class of Individuals: Primary decision makers of businesses that participate in business surveys.

Purpose: The personal information is used to produce statistical data that help shed light on various gaps in the economy for a variety of minority groups, and serves to inform evidence-based decisions on funding and support for specific groups of businesses. Personal information is collected pursuant to the Statistics Act (Sections 3, 7, 8).

Consistent Uses: When collected from the primary decision maker directly and with their informed consent, this sociodemographic personal information may be shared with provincial and territorial statistical agencies and other government organizations that have demonstrated a requirement to use the data, and as permitted under the provisions of Sections 11 or 12 of the Statistics Act.

Retention and Disposal Standards: Information is retained until it is no longer required for statistical purposes and then it is destroyed.

RDA Number: 2007/001

Related Record Number: To be assigned by Statistics Canada

TBS Registration: To be assigned by TBS

Bank Number: StatCan PPU 166

Description of statistical activity

The Survey of Advanced Technology (SAT) and the Survey of Innovation and Business Strategy (SIBS)are mandatory business surveys conducted under the authority of the Statistics Act. The data collected on the surveys covers the adoption, use, development and barriers to adoption of various advanced technologies as well as business innovation and strategy. Due to the need for more disaggregated data in terms of what types of companies are falling behind and require support in technology adoption and innovation, a section was added to the 2022 reference year surveys on the characteristics of the primary decision-maker of the business, which is voluntary for the respondent to answer.

These two survey questionnaires should be completed by the primary decision-maker or the person most familiar with advanced technologies or innovation. This person could be the entrepreneur, Chief Executive Officer (CEO), senior manager, Chief Information Officer (CIO), operations manager or anyone else in an equivalent position in the enterprise. Depending on the company size, the primary decision-maker could be the majority owner, chairman of the board of directors, or general manager of this business. The respondent will be asked to confirm if they are the primary decision maker. In some cases, the primary decision-maker may not be the respondent of the survey; therefore, the respondent is answering these questions to the best of their knowledge.

  • Gender (Male, female, another gender)
  • Sexual and gender diversity (e.g. Identifies as LGBTQ2+)
  • Indigenous Identity (First Nations, Métis, Inuk (Inuit))
  • Visible Minority
  • Persons with a disability
  • New Canadian
  • Highest level of education (only for SAT)
  • Age group (10-year bracket) (only for SAT)

All of these questions in this section are voluntary and have the option of "Don't know" as a response. In addition, these voluntary questions will not be shared as microdata with any organizations outside of Statistics Canada.

The questions have been adapted in collaboration with the Harmonized Content team at Statistics Canada to meet the needs of our business survey. Harmonized content modules contain standard concepts, definitions, classification and wording for multiple collection modes. These questions will shed light on the gaps in the adoption and use of advanced technologies as well as gaps in business innovation for a variety of minority groups. This would allow government departments to make evidence-based decisions on funding and support for specific groups of businesses.

Reason for supplement

While the Generic Privacy Impact Assessment (PIA) addresses most of the privacy and security risks related to statistical activities conducted by Statistics Canada, this supplement is required because these are business surveys that will collect personal information about the primary decision-maker of the business, such as gender, sexual and gender diversity, ethnicity, age group and level of education of an individual indirectly from the respondent business survey contact. As is the case with all PIAs, Statistics Canada's privacy framework ensures that elements of privacy protection and privacy controls are documented and applied.

Necessity and Proportionality

The Survey of Advanced Technology and the Survey of Innovation and Business Strategy will collect information on the characteristics of the business's primary decision-maker, such as gender, sexual and gender diversity, ethnicity, age group and level of education. This personal information is provided by a respondent who may or may not be the primary decision-maker. A question will be asked to confirm if the business respondent is the primary decision maker at the end of the personal information section. The collection of the characteristics of the business's primary decision-maker can be justified against Statistics Canada's Necessity and Proportionality Framework:

1. Necessity

In the 2021 Federal budget, Statistics Canada received funding to produce disaggregated data to identify how minority groups fare compared to their non-minority counterparts. Stakeholders, such as Innovation, Science and Economic Development Canada (ISED), have further expressed a need to understand whether businesses owned by minority groups or whose primary decision maker is part of a minority group perform differently than their non-minority counterparts.

The collection of the characteristics of the business's primary decision maker would benefit Canadians as it would allow light to be shed on the gaps in the adoption and use of advanced technologies and in business innovation for a variety of businesses led by minority groups. This would allow government departments to make evidence-based decisions on funding and support for specific groups of businesses.

2. Effectiveness - Working assumptions

The characteristics of the business's primary decision-maker are collected with a sample of about 13,000 enterprises for SAT and 15,000 enterprises for SIBS. This is the first time this information will be collected for either surveys. The response to these personal information questions is voluntary. Prior to collection, a pre-contact process will be administrated to maximize the probability that the selected respondent for the survey is the primary decision-maker of the business. In some cases, the primary decision-maker may not be the respondent of the survey; therefore, the respondent is answering these questions to the best of their knowledge. The personal information that will be collected includes gender, sexual and gender diversity of the primary decision-maker, as well as if the primary decision-maker identifies as First Nations, Métis or Inuk, if they are a visible minority, have a disability or are a new Canadian. The majority of the questions are written in a Yes/No format. The highest level of education and the age group of the primary decision-maker is also included in this section. The respondent has the option to select the response "Don't know" for all questions.

The purpose of these questions is to disaggregate data related to Canadian businesses whose primary decision maker belongs to a minority group. It is important to note that there will be no statistics published relating to the count or proportion of business owners by these categories (e.g. number or Percentage of businesses whose primary decision-maker is indigenous). Rather, these variables will be used to stratify the data and produce estimates on technology adoption and business innovation by these categories.

3. Proportionality

The data collected will allow government departments to understand the gaps in the adoption and use of advanced technologies as well as gaps in business innovation for a variety of businesses led by minority groups. This would allow government departments to make evidence-based decisions on funding and support for specific groups of businesses which is a priority for the federal government.

With the growing need to understand how minority groups are faring in business, business surveys are looking to adopt these questions, as they are part of the standards developed by the Disaggregated Data Action Plan's Standards Working Group. The questions have been adapted in consultation with the Harmonized Content team at Statistics Canada.

In the section related to the characteristics of the primary decision-maker, the respondent is provided with the response category "Don't know" for all questions. The majority of the questions are written to gather a Yes or No response.

The survey does not ask for the personal identifiers of the business's primary decision-maker (e.g. Name, job title or position). Also, its sample size has been determined to be the smallest possible in order to achieve the objectives.

4. Alternatives

The Survey of Advanced Technology and the Survey of Innovation and Business Strategy are mandatory business surveys using the Business Register as the frame. In the 2022 reference year, a new section is added to collect the characteristics of the primary decision-maker, which is voluntary. Alternatives mode of collection of the personal information includes:

  1. Direct collection from the business's primary decision maker through additional screening questions – however, this may limit the response rate and compromise the ability to produce statistics by these minority groups
  2. Linking these characteristics via other surveys or admin files – however, this process is long and complex. The only dataset that has these types of characteristics data is the Census and only a portion of Canadians were asked to respond to the long-form questionnaire where these questions were asked. Thus, the linkage rate will be fairly low.

Mitigation factors

Some questions contained in the Survey of Advanced Technology and the Survey of Innnovation and Business Strategy are considered sensitive as they include health data (disability), ethnic and racial origins and sexual orientation information. The primary decision-maker may not be the respondent of the survey, so the respondent is answering these questions to the best of their knowledge about the primary decision-maker's demographic characteristics. A question will be asked to confirm if the business respondent is the primary decision maker at the end of the personal information section. Thus, the section with these questions is made voluntary and the overall risk of harm to the survey respondents has been deemed manageable with existing Statistics Canada safeguards that are described in Statistics Canada's Generic Privacy Impact Assessment. The respondent also has the option to select the response "Don't know" for all questions. In addition, these voluntary questions will not be shared as microdata with any organizations outside of Statistics Canada.

Conclusion

This assessment concludes that the overall risk of harm to the survey respondents has been deemed manageable with existing Statistics Canada safeguards that are described.

Formal approval

This Supplementary Privacy Impact Assessment has been reviewed and recommended for approval by Statistics Canada's Chief Privacy Officer, Director General for Modern Statistical Methods and Data Science, and Assistant Chief Statistician for the Enterprise Statistics Field.

The Chief Statistician of Canada has the authority for section 10 of the Privacy Act for Statistics Canada and is responsible for the Agency's operations, including the program area mentioned in this Supplementary Privacy Impact Assessment.

This Privacy Impact Assessment has been approved by the Chief Statistician of Canada.

Statistics Canada to hold news conference to present 2021 Census data on linguistic diversity and the use of English and French in Canada

Media advisory

August 10, 2022, OTTAWA, ON

On August 17, 2022, Statistics Canada will release the fourth set of results from the 2021 Census. This release will explore linguistic diversity and use of English and French in Canada.

The release will be published in Statistics Canada's Daily at 8:30 a.m. eastern time on August 17, 2022. Information about subsequent releases throughout 2022 is available at 2021 Census dissemination planning - Release plans.

Statistics Canada officials will hold a news conference to present high-level national, provincial, and territorial findings for the fourth release from the 2021 Census. Officials will be available to answer questions from the media following their remarks.

On August 17 and the following days, Statistics Canada will also grant interviews regarding this 2021 Census data release. Members of the media are invited to submit their requests for interviews and/or custom tabulations ahead of the release date to the Media Hot Line.

Date

August 17, 2022

Time

9:30 AM to 10:30 AM (EDT)

Location

The news conference will be held virtually.

Participation in the question and answer portion of this event is for accredited members of the Canadian Parliamentary Press Gallery only. Media who are not members of the Press Gallery may contact pressres2@parl.gc.ca to request temporary access. A teleconference line is also available for media who wish to listen to the event:

Toll-free dial-in number (Canada/US): 1-866-206-0153
Local dial-in number: 613-954-9003
Participant passcode: 2604049#

Associated link

2021 Census of Population – Backgrounder for Media

Contact

Media Relations
Statistics Canada
statcan.mediahotline-ligneinfomedias.statcan@statcan.gc.ca