Research and Development Personnel

Detailed information for 2000

Status:

Active

Frequency:

Annual

Record number:

5193

Research and Development (R&D) personnel data are essential to assure the availability of pertinent statistical information to monitor science and technology related activities in Canada and to support the development of science and technology policy.

Data release - May 30, 2001

Description

Canada's economic growth and competitiveness, like that of every other industrialized country, is tied to the development of its scientific and technological base. Of all the factors needed for a country's scientific and industrial development, the supply of suitable human resources is unquestionably one of the most vital. Thus, the formulation of science and technology policy requires reliable information on these human resources, especially those engaged in research and development (R&D). The number of R&D personnel is also considered a supplementary measure to intramural expenditures on R&D. The Frascati Manual (2002) states that "... personnel provide concrete measurements for international comparisons of resources devoted to R&D".

It is important to determine the status of these resources on a regular basis. Data on R&D personnel are derived from surveys conducted by Statistics Canada and from estimates based on various data sources. The R&D personnel tables are designed to provide annual measures of full-time equivalent R&D personnel by geography, science type, sector of performance and occupational category.

R&D data are classified into five sectors of performance. This method facilitates the collection of data and also provides information that can be cross referenced between sectors.

The sectors are:

- federal government
- provincial governments (includes provincial research organizations)
- business enterprise
- higher education
- private non-profit organizations

Reference period: Fiscal year

Subjects

  • Human resources in science and technology
  • Research and development
  • Science and technology

Data sources and methodology

Target population

R&D personnel are drawn from a wide variety of occupations. In order to assist analysis on needs and supplies of highly qualified S&T personnel, R&D personnel are classified into three categories. The International Standard Classification of Occupation (ISCO) distinguishes three occupational levels: researchers, technicians and equivalent staff, and other support staff.

- Researchers (scientists and engineers) are engaged in the conception or creation of new knowledge, products, processes, methods and systems. This level also includes managers and administrators engaged in the planning and management of the scientific and technical aspects of a researcher's work. They are usually equal in rank to the researchers and are often former or part-time researchers themselves. Post-graduate students, in particular those performing significant amounts of R&D, are included in this category.

- Technicians and equivalent staff are persons whose main tasks require technical knowledge and experience in one or more fields of engineering, physical and life sciences, or social sciences and humanities. They participate in R&D by performing scientific and technical tasks involving the application of concepts and operational methods, normally under the supervision of researchers. Equivalent staff performs the corresponding R&D tasks under the supervision of researchers in the social sciences and humanities.

- Support staff includes skilled and unskilled craftsmen, secretarial and clerical staff participating in R&D projects or directly associated with such projects. Also included are all managers and administrators dealing mainly with financial and personnel matters and general administration given that their activities are directly supporting R&D. Those providing an indirect service, such as canteen and cleaning staff, should be excluded.

Instrument design

This methodology does not apply.

Sampling

This methodology type does not apply to this statistical program.

Data sources

Data are collected from other Statistics Canada surveys and/or other sources.

A large amount of information from various surveys and statistical programs within the bureau, along with other data, are compiled, integrated and analysed as part of the process.

Suppliers of data within Statistics Canada include the following:

- Federal Science Expenditures and Personnel, Activities in the Social Sciences and Natural Sciences
- Provincial Government Scientific Activities, in the Social Sciences and Natural Sciences
- Provincial Research Organizations
- Research and Development in Canadian Industry
- Research and Development of Canadian Private Non-Profit Organizations
- University and College Academic Staff System (UCASS).

Error detection

Data are checked against previous years. Data are edited to ensure internal and historical logic and consistency and analyzed for trends and validity. However, if editing occurs it is done at the individual sector level, since this product is an aggregate of other statistical data sources.

Imputation

This methodology does not apply.

Estimation

Data are received in aggregate form. For example, not all sectors provide a provincial distribution between technicians and support staff. Therefore the data are estimated proportionally according to national totals. For the higher education sector, R&D personnel are estimated specifically for this product by aggregating hospital and university data to determine the percentage of full-time equivalent time spent on R&D activities through an established methodology incorporating the three ISCO occupations, eight different disciplines and three institutional sizes.

Data are categorized, checked, compiled, analyzed and compared with other sources of economic information. Estimates are reconciled with these various data sources. Since full-time equivalent calculations are based on estimations, the R&D personnel data go through a statistical convergence process. Based on initial significance testing, precision values for full-time R&D personnel are recorded to the nearest tenth. This process is conducted separately by sector, science type and geography, and as a result, the sum of components does not always add to the total.

Quality evaluation

In order to assure the highest quality of the data for R&D personnel, we continually monitor the coverage of our population, to ensure that all sectors in the universe are accounted for. If data are not obtained directly from the respondent many other sources are researched, including funders' reports where available, previous questionnaires or administrative data, and published data such as financial statements.

An example of data quality procedure includes year to year comparison or historical trend analysis of FTE R&D personnel in all sectors.

Disclosure control

Statistics Canada is prohibited by law from releasing any information it collects that could identify any person, business, or organization, unless consent has been given by the respondent or as permitted by the Statistics Act. 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.

In order to prevent any data disclosure, confidentiality analysis is done using the Statistics Canada Generalized Disclosure Control System (G-Confid). G-Confid is used for primary suppression (direct disclosure) as well as for secondary suppression (residual disclosure). Direct disclosure occurs when the value in a tabulation cell is composed of or dominated by few enterprises while residual disclosure occurs when confidential information can be derived indirectly by piecing together information from different sources or data series.

Revisions and seasonal adjustment

When any historical revisions are necessary they are reconciled with the various data sources.

Data accuracy

Coverage errors consist of omissions, duplications and misclassifications of units.

Since most workers do not all spend the same amount of time on R&D, it is necessary to express the number of persons performing R&D in terms of FTE. If only those persons employed in pure R&D are counted, the number of R&D personnel will be understated, just as counting every person who spends part of his or her time on R&D will result in an overstatement. For example, a person devoting a third of time to R&D will be counted as 0.3 of a full-time equivalent.

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