Alternative Measures Survey for Adults and Youth

Detailed information for 1998-1999





Record number:


This survey collects data on the information on the use of Alternative Measures (AM) in Canada. These data provide important indicators as to the nature and characteristics of caseflow in youth corrections and are of use to agencies responsible for the delivery of these services, the media and the public.

Data release - July 28, 2000


This survey collects information on the use of Alternative Measures(AM) in Canada.

Statistical activity

The survey is currently administered as part of the National Justice Statistics Initiative (NJSI). Since 1981, the federal, provincial and territorial Deputy Ministers responsible for the administration of justice in Canada, with the Chief Statistician, have been working together in an enterprise known as the NJSI. The mandate of the NJSI is to provide information to the justice community as well as the public on criminal and civil justice in Canada. Although this responsibility is shared among federal, provincial and territorial departments, the lead responsibility for the development of Canada's statistical system remains with Statistics Canada.

Reference period: Fiscal year


  • Children and youth
  • Correctional services
  • Crime and justice
  • Crime and justice (youth)

Data sources and methodology

Instrument design

The AM aggregate data collection tools and data requirements were developed with the assistance of representatives from the federal, provincial and territorial agencies responsible for the delivery of youth correctional services in Canada.

The aggregate tables are sent directly to the respondents who fill in the data manually. Computer-aided data collection techniques are not used other than local programming used to extract administrative data from information systems.


This survey is a census with a cross-sectional design.

This methodology does not apply.

Data sources

Data are collected directly from survey respondents.

Jurisdictions providing aggregate data complete a set of standard data tables, which are used to compile national data on alternative measures cases.

View the Questionnaire(s) and reporting guide(s).


Formal imputation is not performed on the aggregate portion of this survey. Missing data or obvious error situations are resolved in consultation with the local data suppliers.


Formal estimation techniques, whether automated or otherwise, are not performed on this survey. From time to time, estimates are necessary in situations where only partial annual data are available. While survey staff may participate in the development of these estimates, 'estimation' itself is not part of the survey methodology.

Quality evaluation

The incoming data are assessed for completeness, historical inconsistency, the existence of outliers and reasonability.

The measurement and assessment of data quality is a complex undertaking. There are several dimensions to the concept of quality, many potential sources of error and often no comprehensive measures of data quality.

The CCJS relies a great deal on the accuracy of respondent information and their verification of that information. Errors arising in the original recording, coding, keying and transmission of data are difficult to measure and assess. Most of the jurisdictional computer systems incorporate basic editing routines to ensure that data fall into acceptable ranges for quantitative data. In some jurisdictions, look-up tables are used to validate the criminal code offence data. These actions certainly reduce the number of incoming errors to the CCJS but they do not entirely eliminate the errors. Random errors are more difficult to locate and correct compared to the systematic type errors. This last type of error can usually be corrected within the CCJS and feedback is given to the jurisdictions for correction.

Errors in the AM are detected using several strategies. Data incoming to the CCJS are reviewed for the amount of change from one year to the next for the same jurisdiction (where possible). Ratios can be calculated to verify that basic relationships are not dramatically changing over time. For example, the ratio of males to females in some tables should be fairly consistent over time.

For some variables, the amount of data appearing in the published tables is a fraction of the total possible. Data are missing for a variety of reasons. In some variables, the data element is simply not collected by a jurisdiction or it is collected but not available for use in the AM survey. Additional data can also be missing because of invalid responses or codes. Where possible, feedback is given to the jurisdictions in order to improve data quality procedures and processes. Little statistical imputation methodology is currently used to handle missing or inconsistent data.

AM survey staff contact individual jurisdictions regarding problems discovered after initial data processing with the objective to increase the useable amount of data for publication. In some cases, the errors are quickly fixed (a re-coding is done). In other situations, the errors are more difficult to correct with the result being that data from the jurisdiction may not be included in the publication.

Disclosure control

Statistics Canada is prohibited by law from releasing any data which would divulge information obtained under the Statistics Act that relates to any identifiable person, business or organization without the prior knowledge or the consent in writing of that person, business or organization. Various confidentiality rules are applied to all data that are released or published to prevent the publication or disclosure of any information deemed confidential. If necessary, data are suppressed to prevent direct or residual disclosure of identifiable data.

The aggregate portion of the survey does not collect individual person data.

The survey produces high level aggregate data tables with minimal breakdown, and few identifiers (ie. Sex, age, aboriginal, non-aboriginal status). No data suppression currently takes place.

Revisions and seasonal adjustment

This methodology does not apply to this survey.

Data accuracy

This survey collects census data as extracted and compiled by local respondents. Formal data quality indicators, beyond annual respondent verification and review for accuracy and consistency, are not part of the survey methodology.

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