University and College Academic Staff System - Full-time Staff (FT-UCASS)
Detailed information for 2019/2020
The purpose of the survey is to collect national data on selected socio-economic characteristics of full-time academic staff at Canadian universities.
Data release - August 20, 2020 (Preliminary data)
This annual survey collects national comparable information on the number and socio-economic characteristics of full-time teaching staff at Canadian universities. The information is collected for each individual staff member employed by the institution as of October 1st of the academic year. The data collected by this survey are used by a variety of clients with a diversity of needs. Some of these clients include:
- International organizations such as the United Nations Educational, Scientific, and Cultural Organization (U.N.E.S.C.O.), Organization for Economic Co-operation and Development (O.E.C.D.), and the Asian-Pacific Economic Co-operation (A.P.E.C.)
- Federal government departments such as Human Resources and Skills Development Canada( HRSDC), Industry Canada (IC)
- Council of Ministers of Education, Canada (C.M.E.C.)
- National Associations such as Universities Canada (U.C.), Canadian Association of University Teachers (C.A.U.T.), Canadian Association of University Business Officers (C.A.U.B.O.)
- Other federal professional associations
- Government departments responsible for education and labour;
- Provincial associations such as the Council of Ontario Universities (COU) and the Maritime Provinces Higher Education Commission (MPHEC);
- Other provincial professional associations
- Individual researchers and educational planners;
- Individual universities, especially the Institutional Research and Human Resources offices;
- Individual bargaining units representing staff at universities
These clients generally use the information in system-wide studies of employment patterns, gender-based analyses, ageing of the professoriate and implications for renewal, salary analysis for contract negotiations, retention and losses to the system, projection of demand, promotional patterns etc.
Reference period: The reference period is as of October 1st during the survey year.
Collection period: The request for information is sent out in mid-August with a deadline of mid-December.
- Education, training and learning
- Teachers and educators
Data sources and methodology
The target population of this survey is full-time teaching staff in degree-granting institutions whose term of appointment is not less than twelve months. This includes all teachers within faculties, academic staff in teaching hospitals, visiting academic staff in faculties and research staff who have an academic rank and salary similar to teaching staff. Administrative, support staff and librarians are excluded, as are staff solely engaged in research without academic rank and/or whose salary scales are different from teaching staff. Teaching and research assistants are also excluded.
Data elements contained in this survey have been collected since 1937. Specific information on the design, testing and implementation of the survey are unavailable.
This survey is a census with a cross-sectional design.
Data are collected for all units of the target population, therefore no sampling is done.
Responding to this survey is mandatory.
Data are collected directly from survey respondents.
The survey is designed to collect information on the characteristics of full-time teachers in degree-granting institutions. Each year Statistics Canada sends out a written request for the information as listed in the "Data Element Manual". Every public degree granting institution in Canada is asked to submit individual teacher records in an electronic format (usually EXCEL file) to Statistics Canada by the end of December. This data is obtained under the authority of the Statistics Act and is supplied by the institutions according to the record layout included in the data element manual which is appended in this document (in most cases data originates from the Human resource information system in each institution.)
The request for information is sent out in mid-August with a deadline of mid-December. A follow up letter is sent in mid-January to delinquent respondents. If the data have not been submitted by late February, then the respondent receives a series of reminder phone calls until the data are received.
View the Questionnaire(s) and reporting guide(s) .
Data is submitted into a data processing system and is subjected to validity and relationship edits. The most recent data year is compared with past years to detect any unusual or unexpected changes. For those records that don't pass the edits, data is passed back to the institution for verification.
Once the data is complete, the file is finalized and summary tables are generated and sent for review by the respondent.
Once the respondent is satisfied with the data, they sign an authorization form that allows data to be released at the institution level.
No imputation is done for this survey.
The University and College Academic Staff System (UCASS) is a census produced from administrative data and is not subject to non-response. As such, estimation weights are not used to produce estimates for UCASS.
Population parameters are produced by running counts and frequencies of full-time academic staff in degree-granting institutions whose term of employment is not less than twelve months. Cross tabulations of variables also describe population parameters.
During the data processing phase, Statistics Canada performs a number of validation activities to ensure accuracy and coherence. This includes comparing the most recent data with data in past years to detect any unusual or unexpected changes. As well, a number of relationship edits are performed that isolate any outliers and these are verified with the respondent. Finally for each respondent, summary tables are compiled from their data for their review and approval to ensure consistency.
Statistics Canada is prohibited by law from releasing any data that 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.
Rounding and cell suppression are used to protect confidentiality of individuals.
To release the data at the institutional level, institutions must authorize Statistics Canada in writing to release their information.
To ensure the confidentiality of the individuals, data at the institutional level are not released for any institution with fewer than 100 full-time teaching staff. For institutions with more than 100 staff, the data are available at the institutional level however, information is processed in such a way that results are suppressed where there are too few individuals. More specifically, measures have been taken to ensure that no one individual or their salary can be identified or extrapolated.
Revisions and seasonal adjustment
This methodology type does not apply to this survey.
The University and College Academic Staff System (UCASS) is a census produced from administrative data and, as such, is not subject to sampling error. The UCASS is however subject to some other non-sampling errors. More specifically, the UCASS is subject to measurement errors and processing errors. Since the target population of UCASS is very stable and the survey is mandatory, the risk of under coverage is minimized.
Coverage errors are minimized by ensuring that the UCASS survey frame corresponds to that of the Postsecondary Student Information System (PSIS).
The University and College Academic Staff System (UCASS) is a census produced from administrative data and, as such, is not subject to sampling error.
The UCASS is however subject to some other non-sampling errors. More specifically, the UCASS is subject to measurement errors and processing errors. To minimize these, Data is submitted into a data processing system and is subjected to validity and relationship edits. The most recent data year is compared with past years to detect any unusual or unexpected changes. For those records that don't pass the edits, data is passed back to the institution for verification.