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Integrated Criminal Court Survey: Interactive Dashboard on Annual Key Indicators

The Integrated Criminal Court Survey: Interactive Dashboard on Annual Key Indicators provides an overview of the annual data on criminal courts program in Canada. The dashboard features statistics on the complexity, the processing time and the outcome of cases in youth courts and adult criminal courts.

Integrated Criminal Court Survey: Interactive Dashboard on Preliminary Quarterly Data

The Integrated Criminal Court Survey: Interactive Dashboard on Preliminary Quarterly Data provides an overview of the preliminary quarterly data on criminal courts program in Canada. The dashboard features statistics on the complexity, the processing time and the outcome of cases in youth courts and adult criminal courts.

Integrated Business Statistics Program (IBSP)

Reporting Guide

This guide is designed to assist you as you complete the 2018 Annual Survey of Research and Development in Canadian Industry – Industrial Non-profit Organizations. If you need more information, please call the Statistics Canada Help Line at the number below.

Help Line: 1-800-972-9692

Your answers are confidential.

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

Statistics Canada will use information from this survey for statistical purposes.

NOTE:

  1. If this organization performs in-house research and development (R&D) and outsources R&D, complete all questions.
  2. If this organization performs in-house research and development (R&D) and does not outsource R&D, complete question 1-6, 9-20.
  3. If this organization outsources research and development (R&D) and does not perform in-house R&D, complete questions 1-4,6-8, 13, 17-20.
  4. If this organization does not perform in-house research and development (R&D) and does not outsource R&D, complete questions 1-4, 6, 13, 17-18 and 20.

For this survey

'In-house R&D' refers to

Expenditures within Canada for R&D performed within this organization by:

  • employees (permanent, temporary or casual)
  • self-employed individuals or contractors who are working on-site on this organization's R&D projects

'Outsourced R&D' refers to

Payments made within or outside Canada to other companies, organizations or individuals to fund R&D performance:

  • grants
  • fellowships
  • contracts

Reporting period information

Here are some examples of common fiscal periods that fall within the targeted dates:

  • May 1, 2017 to April 30, 2018
  • July 1, 2017 to June 30, 2018
  • October 1, 2017 to September 30, 2018
  • January 1, 2018 to December 31, 2018
  • February 1, 2018 to January 31, 2019
  • April 1, 2018 to March 31, 2019

Here are other examples of fiscal periods that fall within the required dates:

  • September 18, 2017 to September 15, 2018 (e.g., floating year-end)
  • June 1, 2018 to December 31, 2019 (e.g., a newly opened organization)

Definitions and Concepts

Research and experimental development (R&D) comprise creative and systematic work undertaken in order to increase the stock of knowledge – including knowledge of humankind, culture and society – and to devise new applications of available knowledge.

R&D is performed in the natural sciences, engineering, social sciences and humanities. There are three types of R&D activities: basic research, applied research and experimental development.

Activities included and excluded from R&D

Inclusions

Prototypes

Include design, construction and operation of prototypes, provided that the primary objective is to make further improvements or to undertake technical testing. Exclude if the prototype is for commercial purposes.

Pilot plants

Include construction and operation of pilot plants, provided that the primary objective is to make further improvements or to undertake technical testing. Exclude if the pilot plant is intended to be operated for commercial purposes.

New computer software or significant improvements/modifications to existing computer software

Includes technological or scientific advances in theoretical computer sciences; operating systems e.g., improvement in interface management, developing new operating system or converting an existing operating system to a significantly different hardware environment; programming languages; and applications if a significant technological change occurs.

Contracts

Include all contracts which require R&D. For contracts which include other work, report only the R&D costs.

Research work in the social sciences

Include if projects are employing new or significantly different modelling techniques or developing new formulae, analyzing data not previously available or applying new research techniques, development of community strategies for disease prevention, or health education.

Exclude:

  • routine analytical projects using standard techniques and existing data
  • routine market research
  • routine statistical analysis intended for on-going monitoring of an activity.

Exclusions

Routine analysis in the social sciences including policy-related studies, management studies and efficiency studies

Exclude analytical projects of a routine nature, with established methodologies, principles and models of the related social sciences to bear on a particular problem (e.g., commentary on the probable economic effects of a change in the tax structure, using existing economic data; use of standard techniques in applied psychology to select and classify industrial and military personnel, students, etc., and to test children with reading or other disabilities).

Consumer surveys, advertising, market research

Exclude projects of a routine nature, with established methodologies intended for commercialization of the results of R&D.

Routine quality control and testing

Exclude projects of a routine nature, with established methodologies not intended to create new knowledge, even if carried out by personnel normally engaged in R&D.

Pre-production activities such as demonstration of commercial viability, tooling up, trial production, and trouble shooting

Although R&D may be required as a result of these steps, these activities are excluded.

Prospecting, exploratory drilling, development of mines, oil or gas wells

Include only if for R&D projects concerned with new equipment or techniques in these activities, such as in-situ and tertiary recovery research.

Engineering

Exclude engineering unless it is in direct support of R&D.

Design and drawing

Exclude design and drawing unless it is in direct support of R&D.

Patent and license work

Exclude all administrative and legal work connected with patents and licenses.

Cosmetic modifications or style changes to existing products

Exclude if no significant technical improvement or modification to the existing products has occurred.

General purpose or routine data collection

Exclude projects of a routine nature, with established methodologies intended for on-going monitoring of an activity.

Routine computer programming, systems maintenance or software application

Exclude projects of a routine nature, with established methodologies intended to support on-going operations.

Routine mathematical or statistical analysis or operations analysis

Exclude projects of a routine nature, with established methodologies intended for on-going monitoring of an activity.

Activities associated with standards compliance

Exclude projects of a routine nature, with established methodologies intended to support standards compliance.

Specialized routine medical care such as routine pathology services

Exclude projects of a routine nature, with established methodologies intended for on-going monitoring of an activity.

In-house R&D expenditures within Canada (Q5 - Q8)

In-house R&D expenditures are composed of current in-house R&D expenditures and capital in-house R&D expenditures.

Current in-house R&D expenditures

Include:

  • wages, salaries, benefits and fringe benefits, materials and supplies
  • services to support R&D, including on-site R&D consultants and contactors
  • necessary background literature
  • minor scientific equipment
  • associated administrative overhead costs.

a. Wages, salaries of permanent, temporary and casual R&D employees

Include benefits and fringe benefits of employees engaged in R&D activities. Benefits and fringe benefits include bonus payments, holiday or vacation pay, pension fund contributions, other social security payments, payroll taxes, etc.

b. Services to support R&D

Include:

  • payments to on-site R&D consultants and contractors working under the direct control of your organization
  • other services including indirect services purchased to support in-house R&D such as security, storage, repair, maintenance and use of buildings and equipment
  • computer services, software licensing fees and dissemination of R&D findings.

c. R&D materials

Include:

  • water, fuel, gas and electricity
  • materials for creation of prototypes
  • reference materials (books, journals, etc.)
  • subscriptions to libraries and data bases, memberships to scientific societies, etc.
  • cost of outsourced (contracted out or granted) small R&D prototypes or R&D models
  • materials for laboratories (chemicals, animals, etc.)
  • all other R&D-related materials.

d. All other current R&D costs including overhead

Include administrative and overhead costs (e.g., office, post and telecommunications, internet, insurance), prorated if necessary to allow for non-R&D activities within the organization.

Exclude:

  • interest charges
  • value-added taxes (goods and services tax (GST) or harmonized sales tax (HST)).

Capital in-house R&D expenditures

Capital in-house R&D expenditures are the annual gross amount paid for the acquisition of fixed assets that are used repeatedly, or continuously in the performance of R&D for more than one year. Report capital in-house R&D expenditures in full for the period when they occurred.

Include costs for software, land, buildings and structures, equipment, machinery and other capital costs.

Exclude capital depreciation.

e. Software

Include applications and systems software (original, customized and off-the-shelf software), supporting documentation and other software-related acquisitions.

f. Land acquired for R&D including testing grounds, sites for laboratories and pilot plants.

g. Buildings and structures that are constructed or purchased for R&D activities or that have undergone major improvements, modifications, renovations and repairs for R&D activities.

h. Equipment, machinery and all other capital

Include major equipment, machinery and instruments, including embedded software, acquired for R&D activities.

Outsourced (contracted out or granted) R&D expenditures (Q9 - Q12)

Include payments made through contracts, grants donations and fellowships to another company, organization or individual to purchase or fund R&D activities.

Exclude expenditures for on-site R&D contractors.

  1. Companies include all incorporated for-profit businesses and government business enterprises providing products in the market at market rates.
  2. Private non-profit organizations include voluntary health organizations, private philanthropic foundations, associations and societies and research institutes. They are not-for-profit organizations that serve the public interest by supporting activities related to public welfare (such as health, education, the environment).
  3. Industrial research institutes or associations include all non-profit organizations that serve the business sector, with industrial associations frequently consisting of their membership.
  4. Federal government includes all federal government departments and agencies. It excludes federal government business enterprises providing products in the market.
  5. Provincial or territorial governments include all provincial or territorial government ministries, departments and agencies. It excludes provincial or territorial government business enterprises providing products in the market.
  6. Provincial or territorial research organizations are organizations created under provincial or territorial law which conduct or facilitate research on behalf of the province or territory.
  7. Other organizations – individuals, non-university educational institutions, foreign governments including ministries, departments and agencies of foreign governments.

Sources of funds for in-house R&D expenditures in 2018 (Q17)

Include Canadian and foreign sources.

Exclude:

  • payments for outsourced (contracted out or granted) R&D, which should be reported in question 10
  • capital depreciation.
a. Funds from this organization
Amount contributed by this organization to R&D performed within Canada (include interest payments and other income, land, buildings, machinery and equipment (capital expenditures) purchased for R&D).
b. Funds from member companies or affiliates
Amount received from member organizations and affiliated organizations used to perform R&D within Canada (include annual fees and sustaining grants, land, buildings, machinery and equipment (capital expenditures) purchased for R&D).
c. Federal government grants or funding
Funds received from the federal government in support of R&D activities not connected to a specific contractual deliverable.
d. Federal government contracts
Funds received from the federal government in support of R&D activities connected to a specific contractual deliverable.
e. R&D contract work for companies
Funds received from companies to perform R&D on their behalf.
f. Provincial or territorial government grants or funding
Funds received from the provincial or territorial government in support of R&D activities not connected to a specific contractual deliverable.
g. Provincial or territorial government contracts
Funds received from the provincial or territorial government in support of R&D activities connected to a specific contractual deliverable.
h. R&D contract work for private non-profit organizations
Funds received from non-profit organizations to perform R&D on their behalf.
i. Other sources
Funds received from all other sources not previously classified.

In-house R&D expenditures by fields of research and development in 2018 (Q19)

Exclude:

  • payments for outsourced (contracted out or granted) R&D, which should be reported in question 10
  • capital depreciation.

Natural and formal sciences

Mathematics, physical sciences, chemical sciences, earth and related environmental sciences, biological sciences, other natural sciences.

Exclude computer sciences, information sciences and bioinformatics (to be reported at lines s and t).

  1. Mathematics: pure mathematics, applied mathematics, statistics and probability.
  2. Physical sciences: atomic, molecular and chemical physics, interaction with radiation, magnetic resonances, condensed matter physics, solid state physics and superconductivity, particles and fields physics, nuclear physics, fluids and plasma physics (including surface physics), optics (including laser optics and quantum optics), acoustics, astronomy (including astrophysics, space science).
  3. Chemical sciences: organic chemistry, inorganic and nuclear chemistry, physical chemistry, polymer science and plastics, electrochemistry (dry cells, batteries, fuel cells, metal corrosion, electrolysis), colloid chemistry, analytical chemistry.
  4. Earth and related environmental sciences: geosciences, geophysics, mineralogy and palaeontology, geochemistry and geophysics, physical geography, geology and volcanology, environmental sciences, meteorology, atmospheric sciences and climatic research, oceanography, hydrology and water resources.
  5. Biological sciences: cell biology, microbiology and virology, biochemistry, molecular biology and biochemical research, mycology, biophysics, genetics and heredity (medical genetics under medical biotechnology), reproductive biology (medical aspects under medical biotechnology), developmental biology, plant sciences and botany, zoology, ornithology, entomology and behavioural sciences biology, marine biology, freshwater biology and limnology, ecology and biodiversity conservation, biology (theoretical, thermal, cryobiology, biological rhythm), evolutionary biology.
  6. Other natural sciences: other natural sciences.

Engineering and Technology

Civil engineering, electrical engineering, electronic engineering and communications technology, mechanical engineering, chemical engineering, materials engineering, medical engineering, environmental engineering, environmental biotechnology, industrial biotechnology, nanotechnology, other engineering and technologies.

Exclude software engineering and technology (to be reported at line r).

  1. Civil engineering: civil engineering, architecture engineering, municipal and structural engineering, transport engineering.
  2. Electrical engineering, electronic engineering and communications technology: electrical and electronic engineering, robotics and automatic control, micro-electronics, semiconductors, automation and control systems, communication engineering and systems, telecommunications, computer hardware and architecture.
  3. Mechanical engineering: mechanical engineering, applied mechanics, thermodynamics, aerospace engineering, nuclear-related engineering (nuclear physics under Physical sciences), acoustical engineering, reliability analysis and non-destructive testing, automotive and transportation engineering and manufacturing, tooling, machinery and equipment engineering and manufacturing, heating, ventilation and air conditioning engineering and manufacturing.
  4. Chemical engineering: chemical engineering (plants, products), chemical process engineering.
  5. Materials engineering: materials engineering and metallurgy, ceramics, coating and films (including packaging and printing), plastics, rubber and composites (including laminates and reinforced plastics), paper and wood and textiles, construction materials (organic and inorganic).
  6. Medical engineering: medical and biomedical engineering, medical laboratory technology (excluding biomaterials, which should be reported under Industrial biotechnology).
  7. Environmental engineering: environmental and geological engineering, petroleum engineering (fuel, oils), energy and fuels, remote sensing, mining and mineral processing, marine engineering, sea vessels and ocean engineering.
  8. Environmental biotechnology: environmental biotechnology, bioremediation, diagnostic biotechnologies in environmental management (DNA chips and bio-sensing devices).
  9. Industrial biotechnology: industrial biotechnology, bioprocessing technologies, biocatalysis and fermentation bioproducts (products that are manufactured using biological material as feedstock), biomaterials (bioplastics, biofuels, bioderived bulk and fine chemicals, bio-derived materials).
  10. Nanotechnology: nano-materials (production and properties), nano-processes (applications on nano-scale).
  11. Other engineering and technologies: food and beverages, oenology, other engineering and technologies.

Software-related sciences and technology

Software engineering and technology, computer sciences, information technology and bioinformatics.

  1. Software engineering and technology: computer software engineering, computer software technology, and other related computer software engineering and technologies.
  2. Computer sciences: computer science, artificial intelligence, cryptography, and other related computer sciences.
  3. Information technology and bioinformatics: information technology, informatics, bioinformatics, biomathematics, and other related information technologies.

Medical and health sciences

Basic medicine, clinical medicine, health sciences, medical biotechnology, other medical sciences.

  1. Basic medicine: anatomy and morphology (plant science under Biological science), human genetics, immunology, neurosciences, pharmacology and pharmacy and medicinal chemistry, toxicology, physiology and cytology, pathology.
  2. Clinical medicine: andrology, obstetrics and gynaecology, paediatrics, cardiac and cardiovascular systems, haematology, anaesthesiology, orthopaedics, radiology and nuclear medicine, dentistry, oral surgery and medicine, dermatology, venereal diseases and allergy, rheumatology, endocrinology and metabolism and gastroenterology, urology and nephrology, and oncology.
  3. Health sciences: health care sciences and nursing, nutrition and dietetics, parasitology, infectious diseases and epidemiology, occupational health.
  4. Medical biotechnology: health-related biotechnology, technologies involving the manipulation of cells, tissues, organs or the whole organism, technologies involving identifying the functioning of DNA, proteins and enzymes, pharmacogenomics, gene-based therapeutics, biomaterials (related to medical implants, devices, sensors).
  5. Other medical sciences: forensic science, other medical sciences.

Agricultural Sciences

Agriculture, forestry and fisheries sciences, animal and dairy sciences, veterinary sciences, agricultural biotechnology, other agricultural sciences.

  1. Agriculture, forestry and fisheries sciences: agriculture, forestry, fisheries and aquaculture, soil science, horticulture, viticulture, agronomy, plant breeding and plant protection.
  2. Animal and dairy sciences: animal and dairy science, animal husbandry.
  3. Veterinary sciences: veterinary science (all).
  4. Agricultural biotechnology: agricultural biotechnology and food biotechnology, genetically modified (GM) organism technology and livestock cloning, diagnostics (DNA chips and biosensing devices), biomass feedstock production technologies and biopharming.
  5. Other agricultural sciences: other agricultural sciences.

Social sciences and humanities

Psychology, educational sciences, economics and business, other social sciences, humanities.

  1. Psychology: cognitive psychology and psycholinguistics, experimental psychology, psychometrics and quantitative psychology, and other fields of psychology.
  2. Educational sciences: education, training and other related educational sciences.
  3. Economics and business: micro-economics, macro-economics, econometrics, labour economics, financial economics, business economics, entrepreneurial and business administration, management and operations, management sciences, finance and all other related fields of economics and business
  4. Other social sciences: anthropology (social and cultural) and ethnology, demography, geography (human, economic and social), planning (town, city and country), management, organization and methods (excluding market research unless new methods/techniques are developed), law, linguistics, political sciences, sociology, miscellaneous social sciences and interdisciplinary, and methodological and historical science and technology activities relating to subjects in this group.
  5. Humanities: history (history, prehistory and history, together with auxiliary historical disciplines such as archaeology, numismatics, palaeography, genealogy, etc.), languages and literature (ancient and modern), other humanities (philosophy (including the history of science and technology)), arts (history of art, art criticism, painting, sculpture, musicology, dramatic art excluding artistic 'research' of any kind), religion, theology, other fields and subjects pertaining to the humanities, and methodological, historical and other science and technology activities relating to the subjects in this group.

In-house R&D personnel in 2018 (Q71 - Q73)

R&D personnel

Include:

  • permanent, temporary and casual R&D employees
  • independent on-site R&D consultants and contractors working in your organization's offices, laboratories, or other facilities
  • employees engaged in R&D-related support activities.

Researchers and research managers are composed of

  1. Scientists, social scientists, engineers and researchers are professionals engaged in the conception or creation of new knowledge. They conduct research and improve or develop concepts, theories, models, techniques instrumentation, software or operational methods. They may be certified by provincial or territorial educational authorities, provincial, territorial or national scientific or engineering associations.
  2. Senior research managers plan or manage R&D projects and programs. They may be certified by provincial or territorial educational authorities, provincial, territorial or national scientific or engineering associations.

R&D technical, administrative and support staff are composed of:

  1. Technicians and technologists and research assistants are persons whose main tasks require technical knowledge and experience in one or more fields of engineering, the physical and life sciences, or the social sciences, humanities and the arts. They participate in R&D by performing scientific and technical tasks involving the application of concepts, operational methods and the use of research equipment, normally under the supervision of researchers. They may be certified by provincial or territorial educational authorities, provincial, territorial or national scientific or engineering associations.
  2. Other R&D technical, administrative support staff include skilled and unskilled craftsmen, and administrative, secretarial and clerical staff participating in R&D projects or directly associated with such projects.

On-site R&D consultants and contractors are individuals hired 1) to perform project-based work or to provide goods at a fixed or ascertained price or within a certain time or 2) to provide advice or services in a specialized field for a fee and, in both cases, work at the location specified and controlled by the contracting company or organization.

Full-time equivalent (FTE)

R&D may be carried out by persons who work solely on R&D projects or by persons who devote only part of their time to R&D, and the balance to other activities such as testing, quality control and production engineering. To arrive at the total effort devoted to R&D in terms of personnel, it is necessary to estimate the full-time equivalent of these persons working only part-time in R&D.

FTE (full-time equivalent): Number of persons who work solely on R&D projects + the time of persons working only part of their time on R&D.

Example calculation: If out of four scientists engaged in R&D work, one works solely on R&D projects and the remaining three devote only one quarter of their working time to R&D, then: FTE = 1 + 1/4 + 1/4 + 1/4 = 1.75 scientists.

Technology and technical assistant payments in 2018 (Q74 - Q76)

Definitions (equivalent to the Canadian Intellectual Property Office: http://www.ic.gc.ca/eic/site/cipointernet-internetopic.nsf/eng/home)

a. Patent
Government grant giving the right to exclude others from making, using or selling an invention.
b. Copyright
Legal protection for literary, artistic, dramatic or musical works, computer programs, performer's performances, sound recordings, and communication signals.
c. Trademark
A word, symbol or design, or combination of these, used to distinguish goods or services of one person or organization from those of others in the marketplace.
d. Industrial design
Legal protection against imitation of the shape, pattern, or ornamentation of an object.
e. Integrated circuit topography
Three-dimensional configurations of the elements and interconnections embodied in an integrated circuit product.
f. Original software
Computer programs and descriptive materials for both systems and applications. Original software can be created in-house or outsourced and includes packaged software with customization.
g. Packaged or off-the-shelf software
Packaged software purchased for organizational use and excludes software with customization.
h. Databases
Data files organized to permit effective access and use of the data.
i. Other
Technical assistance, industrial processes and know-how.

Energy-related R&D by area of technology (Q23 - Q70)

Fossil Fuels

Crude oils and natural gas exploration, crude oils and natural gas production, oil sands and heavy crude oils surface and sub-surface production and separation of the bitumen, tailings management, refining, processing and upgrading, coal production, separation and processing, transportation of fossil fuels.

a. Crude oils and natural gas exploration
Include development of advanced exploration methods (geophysical, geochemical, seismic, magnetic) for on-shore and off-shore prospecting.
b. Crude oil and natural gas production and storage, include enhanced recovery natural gas production
Include on-shore and off-shore deep drilling equipment and techniques for conventional oil and gas, secondary and tertiary recovery of oil and gas, hydro fracturing techniques, processing and cleaning of raw product, storage on remote platforms (e.g., Arctic, off-shore), safety aspects of offshore platforms.
c. Oil sands and heavy crude oils surface and sub-surface production and separation of the bitumen, tailings management
Include surface and in-situ production (e.g., SAGD), tailings management.
d. Refining, processing and upgrading of fossil fuels
Include processing of natural gas to pipeline specifications, and refining of conventional crude oils to refined petroleum products (RPPs), and the upgrading of bitumen and heavy oils either to synthetic crude oil or to RPPs. Upgrading may be done at an oil sands plant, regional merchant upgraders or integrated into a refinery producing RPPs.
e. Coal production, separation and processing
Include coal, lignite and peat exploration, deposit evaluation techniques, mining techniques, separation techniques, coking and blending, other processing such as coal to liquids, underground (in-situ) gasification.
f. Transportation of fossil fuels
Include transport of gaseous, liquid and solid hydrocarbons via pipelines (land and submarine) and their network evaluation, safety aspects of LNG transport and storage.

Renewable energy resources

Solar photovoltaics (PV), solar thermal-power and high-temperature applications, solar heating and cooling, wind energy, bio-energy – biomass production, bio-energy – biomass conversion to fuels, bio-energy – biomass conversion to heat and electricity, other bio-energy, small hydro (less than 10 MW), large hydro (greater than or equal to 10 MW), other renewable energy.

a. Solar photovoltaics (PV)
Include solar cell development, PV-module development, PV-inverter development, building-integrated PV-modules, PV-system development, other.
b. Solar thermal-power and high-temperature applications
Include solar chemistry, concentrating collector development, solar thermal power plants, high-temperature applications for heat and power.
c. Solar heating and cooling
Include daylighting, passive and active solar heating and cooling, collector development, hot water preparation, combined-space heating, solar architecture, solar drying, solar-assisted ventilation, swimming pool heating, low-temperature process heating, other.
d. Wind energy
Include technology development, such as blades, turbines, converters structures, system integration, other.
e. Bio-energy – Biomass production and transport
Include improvement of energy crops, research on bio-energy production potential and associated land-use effects, supply and transport of bio-solids, bio-liquids, biogas and bio-derived energy products (e.g., ethanol, biodiesel), compacting and baling, other.
f. Bio-energy – Biomass conversion to transportation fuel
Include conventional bio-fuels, cellulosic-derived alcohols, biomass gas-to-liquids, other energy-related products and by-products.
g. Bio-energy – Biomass conversion to heat and electricity
Include bio-based heat, electricity and combined heat and power (CHP), exclude multi-firing with fossil fuels.
h. Other bio-energy
Include recycling and the use of municipal, industrial and agricultural waste as energy not covered elsewhere.
i. Small hydro – (less than 10 MW)
Include plants with capacity below 10 MW.
j. Large hydro – (greater than or equal to 10 MW)
Include plants with capacity of 10 MW and above.
k. Other renewable energy
Include hot dry rock, hydro-thermal, geothermal heat applications (including agriculture), tidal power, wave energy, ocean current power, ocean thermal power, other.

Nuclear fission and fusion

Materials exploration, mining and preparation, tailings management, nuclear reactors, other fission, fusion.

a. Nuclear materials exploration, mining and preparation, tailings management
Include development of advanced exploration methods (geophysical, geochemical) for prospecting, ore surface and in-situ production, uranium and thorium extraction and conversion, enrichment, handling of tailings and remediation.
b. Nuclear reactors
Include nuclear reactors of all types and related system components.
c. Other fission
Include nuclear safety, environmental protection (emission reduction or avoidance), radiation protection and decommissioning of power plants and related nuclear fuel cycle installations, nuclear waste treatment, disposal and storage, fissile material recycling, fissile materials control, transport of radioactive materials.
d. Fusion
Include all types (e.g., magnetic confinement, laser applications).

Electric Power

Generation in utility sector, combined heat and power in industry and in buildings, electricity transmission, distribution and storage of electricity.

a. Electric power generation in utility sector
Include conventional and non-conventional technology (e.g., pulverised coal, fluidised bed, gasification-combined cycle, supercritical), re-powering, retrofitting, life extensions and upgrading of power plants, generators and components, super-conductivity, magneto hydrodynamic, dry cooling towers, co-firing (e.g., with biomass), air and thermal pollution reduction or avoidance, flue gas cleanup (excluding CO2 removal), CHP (combined heat and power) not covered elsewhere.
b. Electric power - combined heat and power in industry, buildings
Include industrial applications, small scale applications for buildings.
c. Electricity transmission, distribution and storage
Include solid state power electronics, load management and control systems, network problems, super-conducting cables, AC and DC high voltage cables, HVDC transmission, other transmission and distribution related to integrating distributed and intermittent generating sources into networks, all storage (e.g., batteries, hydro reservoirs, fly wheels), other.

Hydrogen and fuel cells

Hydrogen production for process applications, hydrogen production for transportation applications, hydrogen transport and storage, other hydrogen, fuel cells, both stationary and mobile.

a. Hydrogen production for process applications
b. Hydrogen production for transportation applications
c. Hydrogen transport and storage
d. Other hydrogen
Include end uses (e.g., combustion), other infrastructure and systems R&D (refuelling stations).
e. Stationary fuel cells
Include electricity generation, other stationary end-use.
f. Mobile fuel cells
Include portable applications.

Energy efficiency

Industry, residential and commercial, transportation, other energy efficiency.

a. Energy efficiency applications for industry
Include reduction of energy consumption through improved use of energy and/or reduction or avoidance of air and other emissions related to the use of energy in industrial systems and processes (excluding bio-energy-related) through the development of new techniques, new processes and new equipment, other.
b. Energy efficiency for residential, institutional and commercial sectors
Include space heating and cooling, ventilation and lighting control systems other than solar technologies, low energy housing design and performance other than solar technologies, new insulation and building materials, thermal performance of buildings, domestic appliances, other.
c. Energy efficiency for transportation
Includes analysis and optimisation of energy consumption in the transport sector, efficiency improvements in light-duty vehicles, heavy-duty vehicles, non-road vehicles, public transport systems, engine-fuel optimisation, use of alternative fuels (liquid and gaseous, other than hydrogen), fuel additives, diesel engines, Stirling motors, electric cars, hybrid cars, air emission reduction, other.
d. Other energy efficiency
Include waste heat utilisation (heat maps, process integration, total energy systems, low temperature thermodynamic cycles), district heating, heat pump development, reduction of energy consumption in the agricultural sector.

Other energy-related technologies

Carbon capture, transportation and storage for fossil fuel production and processing, electric power generation, industry in end-use sector, energy systems analysis, all other energy-related technologies.

a. Carbon capture, transport and storage related to fossil fuel production and processing
b. Carbon capture, transport and storage related to electric power production
c. Carbon capture, transport and storage related to industry in end-use sector
Include industry in the end-use sector, such as steel production, manufacturing, etc. (exclude fossil fuel production and processing and electric power production).
d. Energy system analysis
Include system analysis related to energy R&D not covered elsewhere, sociological, economical and environmental impact of energy which are not specifically related to one technology area listed in the sections above.
e. All other energy technologies
Include energy technology information dissemination, studies not related to a specific technology area listed above.

Small Area Estimation for Visitor Travel Survey

The Visitor Travel Survey (VTS) provides a full range of statistics on the volume of international visitors to Canada and detailed characteristics of their trips. In recent years, there has been an increased interest in estimating sub-provincial inbound travel spending. Direct estimates of foreign travel spending can be obtained from the VTS, but they would be reliable only if the sample sizes are large enough. Therefore, a Small Area Estimation (SAE) methodology is now used to improve the quality of sub-provincial estimates, using Payment processors' (acquirer) data provided by Destination Canada. This document briefly describes this methodology.

1. Introduction

The VTS was introduced in January 2018 to replace the U.S. and overseas visitors to Canada component of the International Travel Survey (ITS). The objective of the VTS is to provide a full range of statistics on the volume of international visitors to Canada and detailed characteristics of their trips such as expenditures, activities, places visited and length of stay. The target population of the VTS is all U.S. and overseas residents entering Canada. Excluded from the survey's coverage are diplomats and their dependents, refugees, landed immigrants, military, crew and former Canadian residents.

The demand for inbound travel spending estimates at smaller geographical levels has greatly increased in recent years. Standard weighted estimates (or direct estimates) at sub-provincial levels can be obtained from the VTS. However, these direct estimates can be considered reliable as long as the sample size in the area of interest is large enough. To address this issue, a SAE methodology is used to improve the quality of sub-provincial estimates, using Payment processors' data provided by Destination Canada.

SAE methods attempt to produce reliable estimates when the sample size in the area is small. In this application of the methodology, the small area estimate is a function of two quantities: the direct estimate from the survey data, and a prediction based on a model – sometimes referred to as the indirect, or synthetic estimate. The model involves survey data from the geographical area of interest, but also incorporates data from other areas (as input to the model parameters) and auxiliary data. The auxiliary data must come from a source that is independent of the VTS, and it must be available at the appropriate levels of geography. The SAE model uses the Payment processors' data which includes a portion of credit and debit card payments made by international visitors to Canada, as the auxiliary data. More precisely, the Payment data along with the direct survey estimates, are used to derive the small area estimates. For the smallest areas, the direct estimates are not reliable and the small area estimates are driven mostly by the predictions from the model. However, for the largest areas, this is the opposite and the small area estimates tend to be close to the direct estimates.

There are two types of SAE models: area-level (or aggregate) models that relate small area means to area-specific auxiliary variables, and unit-level models that relate the unit values of the study variable to unit-specific auxiliary variables. The VTS uses an area-level model as the auxiliary information (i.e., Payment data) is aggregated.

Section 2 describes the requirements to produce sub-provincial inbound travel spending estimates. In section 3, diagnostics used for model validation and evaluation of small area estimates are briefly discussed.

2. Area-level model

The small area estimates were obtained through the use of the small area estimation module of the generalized software G-ESTFootnote 1 version 2.02 (Estevao et al., 2017a, 2017b). For each area i, three inputs need to be provided to the G-EST in order to obtain small area estimates:

i) Direct estimates θ^i, which are calculated using survey weights
θ^i=ksiwkyk
where yk represents spending by unit k in domain i, and wk is the sampling weights assigned to unit k on the VTS sample

ii) Smoothed variance estimates at the domain of interest, which are obtained by applying a piecewise smoothing approach on the variance estimates that are calculated using mean bootstrap weights

iii) Vector of auxiliary variables zi

For the estimation of inbound travel spending, the domain of interest are defined as: 11 country / country groups × 22 tourism regions / grouped tourism regions

The 11 country / country groups are as follows:

Table 1: Country / country groups
Group Country
1 Australia
2 China
3 Japan
4 South Korea
5 India
6 United Kingdom
7 France
8 Germany
9 Mexico
10 United States
11 Other countries

The 84 tourism regions are grouped into 22 domains, as shown in the following table.

Table 2: Tourism region / Grouped tourism regions
Tourism region / Grouped Tourism Regions Tourism regions Province/Territory
1000 (Newfoundland & Labrador) 001, 005, 010, 015, 020, 099Footnote 2 Newfoundland and Labrador
1100 (Prince Edward Island) 101 Prince Edward Island
1200 (Nova Scotia) 202, 206, 211, 215, 220, 225, 232, 299 Nova Scotia
1300 (New Brunswick) 300, 302, 304, 308, 318, 399 New Brunswick
2400 (Rest of Quebec) 401, 405, 410, 420, 425, 430, 435, 440, 445, 450, 455, 465, 470, 475, 480, 485, 491, 492, 493, 495, 499 Quebec
0415 (Quebec) 415
0460 (Montreal 460
3500 (Rest of Ontario) 502, 511, 516, 526, 531, 536, 541, 551, 556, 560, 565, 570, 599 Ontario
0506 (Niagara Falls and Wine Country) 506
0521 (Greater Toronto Area) 521
0546 (Ottawa and Countryside) 546
4600 (Manitoba) 601, 605, 610, 615, 620, 625, 630, 635, 699 Manitoba
4700 (Saskatchewan) 701, 705, 710, 715, 720, 725, 730, 799 Saskatchewan
4800 (Rest of Alberta) 801, 805, 810, 825, 899 Alberta
0815 (Canadian Rockies) 815
0820 (Calgary and Area) 820
5900 (Rest of British Columbia) 901, 910, 920, 925, 999 British Columbia
0905 (Vancouver, Coast & Mountains) 905
0915 (Kootenay Rockies) 915
6000 (Yukon) 981 Yukon
6100 (Northwest Territories) 991 Northwest Territories
6200 (Nunavut) 992 Nunavut

It should be mentioned that for the VTS, a modification of the basic area-level model, piecewise area-level model, was used. The piecewise area-level is useful when a single linear model does not provide an adequate explanation on the relationship between the variable of interest and the covariates. The area specific auxiliary variable i.e., spending from the Payment data, is partitioned into intervals and a separate line segment is fit to each interval.

3. Evaluation of small area estimates

The accuracy of small area estimates depends on the reliability of the model. It is therefore essential to make a careful assessment of the validity of the model before releasing estimates. For instance, it is important to verify that a linear relationship actually holds between direct estimates from VTS (θ^i) and payment data (zi), at least approximately.

For the VTS, diagnostic plots and tests in the G-EST are used to assess the model, and outliers are identified iteratively by examining the standardized residuals from that model.

A concept that is useful to evaluate the gains of efficiency resulting from the use of the small area estimate θ^iSAE over the direct estimate θ^i is the Mean Square Error (MSE). The MSE is unknown but can be estimated (see Rao and Molina, 2015). Gains of efficiency over the direct estimate are expected when the MSE estimate is smaller than the smoothed variance estimate or the direct variance estimate. In general, the small area estimates in the VTS were significantly more efficient than the direct estimates, especially for the areas with the smallest sample size.

References

Estevao, V., You, Y., Hidiroglou, M., Beaumont, J.-F. (2017a). Small Area Estimation-Area Level Model with EBLUP Estimation- Description of Function Parameters and User Guide. Statistics Canada document.

Estevao, V., You, Y., Hidiroglou, M., Beaumont, J.-F. and Rubin-Bleuer, S. (2017b). Small Area Estimation-Area Level Model with EBLUP Estimation- Methodology Specifications. Statistics Canada document.

Hidiroglou, M. A., Beaumont, J. F., and Yung, W. (2019). Development of a small area estimation system at Statistics Canada. Survey Methodology, 45(1), 101-126.

Rao, J.N.K., and Molina, I. (2015). Small Area Estimation. John Wiley & Sons, Inc., Hoboken, New Jersey.

Statistics Canada. (2017). Monthly Labour Force Survey Small Area Estimation- Documentation to accompany small area estimates. Statistics Canada document.

Statistics Canada protects your privacy: Balancing societal needs for data insights and the protection of your privacy

Infosheet - Statistics Canada protects your privacy: Balancing societal needs for data insights and the protection of your privacy
Description - Statistics Canada protects your privacy: Balancing societal needs for data insights and the protection of your privacy

Modern statistical needs

Collecting data for statistics is more than a century old and keeps evolving. In our Digital Age, your information needs are growing, and new data sources offer new possibilities for information.

Collaboration

Statistics Canada is working with experts from businesses and academia from around the world as well as the Office of the Privacy Commissioner to develop new statistical methods based on necessity and proportionality.

A new framework

The new framework expands on these principles, which have always guided Statistics Canada. It assesses proportionality and data sensitivity, and ensures statistical values, such as the protection of privacy and confidentiality.

Necessity

Statistics Canada produces data that are necessary for governments, municipalities, businesses small and large, and individuals like you to make informed decisions. The agency measures our society, economy and environment.

Proportionality

When we plan surveys, our experts develop data collection strategies that take into account ethical considerations such as privacy, fairness and transparency.

Correctional services statistics

Correctional services Statistics

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Bringing together data, tools and reports to provide you with the latest information on correctional services in Canada.

Correctional services statistics: Interactive dashboard

Correctional services statistics: Interactive dashboard

The Correctional services statistics: Interactive dashboard provides an overview of correctional services programs in Canada. The dashboard features statistics on average daily counts, community and custodial admissions and the characteristics of adults and youth in the correctional system.

Crime and justice statistics

Crime and justice statistics

Crime and justice statistics provides an overview of the information on the subject of Crime and justice at Statistics Canada.

Adult and youth correctional statistics

Adult and youth correctional statistics in Canada, 2018/2019

Adult and youth correctional statistics in Canada, 2020/2021 provides an overview of adult and youth correctional services in Canada in 2020/2021.

Quarterly Survey of Financial Statements (QSFS): Weighted Asset Response Rate - Q2 2018 to Q2 2019

Weighted Asset Response Rate
Table summary
This table displays the results of Weighted Asset Response Rate. The information is grouped by Release date (appearing as row headers), 2018 Q2, Q3 and Q4, and 2019 Q1 and Q2 calculated using percentage units of measure (appearing as column headers).
Release date 2018 2019
Q2 Q3 Q4 Q1 Q2
quarterly (percentage)
August 23, 2019 88.0 85.5 83.5 81.9 65.2
May 24, 2019 88.0 85.5 83.5 67.5 ..
February 26, 2019 77.2 72.1 60.0 .. ..
November 22, 2018 78.5 64.7 .. .. ..
August 23, 2018 70.9 .. .. .. ..
.. not available for a specific reference period
Source: Quarterly Survey of Financial Statements (2501)

Statement outlining results, risks and significant changes in operations, personnel and program

A) Introduction

Statistics Canada's mandate

Statistics Canada ("the agency") is a member of the Innovation, Science and Economic Development portfolio.

Statistics Canada's role is to ensure that Canadians have access to a trusted source of statistics on Canada that meets their highest priority needs.

The agency's mandate derives primarily from the Statistics Act. The Act requires that the agency collects, compiles, analyzes and publishes statistical information on the economic, social, and general conditions of the country and its people. It also requires that Statistics Canada conduct the census of population and the census of agriculture every fifth year, and protects the confidentiality of the information with which it is entrusted.

Statistics Canada also has a mandate to co-ordinate and lead the national statistical system. The agency is considered a leader, among statistical agencies around the world, in co–ordinating statistical activities to reduce duplication and reporting burden.

More information on Statistics Canada's mandate, roles, responsibilities and programs can be found in the 2019–2020 Main Estimates and in the Statistics Canada 2019–2020 Departmental Plan.

The Quarterly Financial Report:

  • should be read in conjunction with the 2019–2020 Main Estimates;
  • has been prepared by management, as required by Section 65.1 of the Financial Administration Act, and in the form and manner prescribed by Treasury Board of Canada Secretariat;
  • has not been subject to an external audit or review.

Statistics Canada has the authority to collect and spend revenue from other federal government departments and agencies, as well as from external clients, for statistical services and products.

Basis of presentation

This quarterly report has been prepared by management using an expenditure basis of accounting. The accompanying Statement of Authorities includes the agency's spending authorities granted by Parliament and those used by the agency consistent with the Main Estimates for the 2019–2020 fiscal year. This quarterly report has been prepared using a special purpose financial reporting framework designed to meet financial information needs with respect to the use of spending authorities.

The authority of Parliament is required before moneys can be spent by the Government. Approvals are given in the form of annually approved limits through appropriation acts or through legislation in the form of statutory spending authority for specific purposes.

The agency uses the full accrual method of accounting to prepare and present its annual departmental financial statements that are part of the departmental results reporting process. However, the spending authorities voted by Parliament remain on an expenditure basis.

B) Highlights of fiscal quarter and fiscal year-to-date results

This section highlights the significant items that contributed to the net increase in resources available for the year, as well as actual expenditures for the quarter ended June 30.

Comparison of gross budgetary authorities and expenditures as of June 30, 2018, and June 30, 2019, in thousands of dollars
Description for Chart 1: Comparison of gross budgetary authorities and expenditures as of June 30, 2018, and June 30, 2019, in thousands of dollars

This bar graph shows Statistics Canada's budgetary authorities and expenditures, in thousands of dollars, as of June 30, 2018 and 2019:

  • As at June 30, 2018
    • Net budgetary authorities: $478,419
    • Vote netting authority: $120,000
    • Total authority: $598,419
    • Net expenditures for the period ending June 30: $129,286
    • Year-to-date revenues spent from vote netting authority for the period ending June 30: $17,347
    • Total expenditures: $146,633
  • As at June 30, 2019
    • Net budgetary authorities: $502,199
    • Vote netting authority: $120,000
    • Total authority: $622,199
    • Net expenditures for the period ending June 30: $139,487
    • Year-to-date revenues spent from vote netting authority for the period ending June 30: $14,623
    • Total expenditures: $154,110

Chart 1 outlines the gross budgetary authorities, which represent the resources available for use for the year as of June 30.

Significant changes to authorities

Total authorities available for 2019–2020 have increased by $23.8 million, or 4.0%, from the previous year, from $598.4 million to $622.2 million (Chart 1). This net increase is mostly the result of the following:

  • An increase of $22.4 million for the 2021 Census of Population program and $8.4 million for the 2021 Census of Agriculture program for new cyclical funding received to cover planning and developmental activities;
  • An increase of $6.3 million for Workload Migration, an initiative approved in 2018–2019 which will migrate the information technology infrastructure to the cloud;
  • An increase of $3.2 million for the Survey of Financial Security and Annual Household Wealth Tables;
  • An increase of $3.0 million for the Renewing and Modernizing Statistics Canada initiative approved in 2018–2019 which will change the way the federal government collects, uses and shares data while ensuring the privacy of Canadians remains protected;
  • A decrease of $6.2 million for the 2016 Census of Population program and $2.2 million for the 2016 Census of Agriculture program due to the cyclical nature of funding that is winding down;
  • A decrease of $6.0 million for the finalisation of retro pay for collective agreements;
  • A decrease of $5.8 million for the Statistical Survey Operations pay equity settlement.

The variance is also explained by the reception of authorities at different quarters throughout the year.

In addition to the appropriations allocated to the agency through the Main Estimates, Statistics Canada also has vote net authority within Vote 1, which entitles the agency to spend revenues collected from other federal government departments, agencies, and external clients to provide statistical services. The vote netting authority is stable at $120 million when comparing the first quarter of fiscal years 2018–2019 and 2019–2020.

Significant changes to expenditures

Year-to-date net expenditures recorded to the end of the first quarter increased by $10.2 million, or 7.9% from the previous year, from $129.3 million to $139.5 million (see Table A: Variation in Departmental Expenditures by Standard Object).

Statistics Canada spent approximately 28% of its authorities by the end of the first quarter, compared with 27% in the same quarter of 2018–2019.

Table A: Variation in Departmental Expenditures by Standard Object (unaudited)
Table summary: This table displays the variance of departmental expenditures by standard object between fiscal 2017-2018 and 2018-2019. The variance is calculated for year to date expenditures as at the end of the first quarter. The row headers provide information by standard object. The column headers provide information in thousands of dollars and percentage variance for the year to date variation.
Departmental Expenditures Variation by Standard Object: Q1 year-to-date variation between fiscal year 2018–2019 and 2019–2020
$'000 %
Note: Explanations are provided for variances of more than $1 million.
(01) Personnel 7,819 6.0
(02) Transportation and communications 949 40.1
(03) Information 258 27.7
(04) Professional and special services 598 12.1
(05) Rentals 875 19.6
(06) Repair and maintenance -31 -24.2
(07) Utilities, materials and supplies -54 -28.7
(08) Acquisition of land, buildings and works -7 -100.0
(09) Acquisition of machinery and equipment -2,025 -71.8
(10) Transfer payments - -
(12) Other subsidies and payments -905 -76.9
Total gross budgetary expenditures 7,477 5.1
Less revenues netted against expenditures:
Revenues -2,724 -15.7
Total net budgetary expenditures 10,201 7.9

Personnel: The increase is mainly due to the ratification of collective agreements and an overall increase in the agency's activities.

Acquisition of machinery and equipment: The decrease is mainly due to a temporary variance related to an invoice for which the cost of the service request has been reduced later in the fiscal year.

Revenues: The decrease is primarily the result of timing differences in the receipt of funds for scheduled key deliverables.

The variance is also explained by timing differences of payments in this period compared to last fiscal year.

C) Risks and uncertainties

Statistics Canada is currently expending significant effort in modernizing its business processes and tools, in order to maintain its relevance and maximize the value it provides to Canadians. As a foundation piece for some of these efforts, the agency is working in collaboration with Shared Services Canada and Treasury Board of Canada Secretariat, Office of the Chief Information Officer, to ensure the agency has access to adequate IT services and support to attain its modernization objectives and successfully transition its infrastructure to the cloud. Activities and related costs are projected based on various assumptions that can change, depending on the nature and degree of work required to accomplish the initiatives. Risks and uncertainties are being mitigated by the agency's strong financial planning management practices and business architecture.

D) Significant changes to operations, personnel and programs

There were no major changes to the departmental operations during this quarter. Minor changes in program activities with financial implications include:

  • The Census program is ramping down operations from the 2016 Census and is in a more advanced planning and testing phase for the 2021 Census. As such, expenditures for this program are increasing.
  • Budget 2018 announced funding for new initiatives. Expenditures related to these new initiatives will ramp up throughout the fiscal year.

Approval by senior officials

Approved by:

Anil Arora, Chief Statistician
Kathleen Mitchell, Acting Chief Financial Officer
Ottawa, Ontario
Signed on: August 21, 2019

Appendix

Statement of Authorities (unaudited)
Table summary: This table displays the departmental authorities for the fiscal years 2019–2020 and 2018–2019. The row headers provide information by type of authority, Vote 105 – Net operating expenditures, Statutory authority and Total Budgetary authorities. The column headers provide information in thousands of dollars for Total available for use for the year ending March 31; used during the quarter ended June 30; and year to date used at quarter-end.
  Fiscal year 2019–2020 Fiscal year 2018–2019
Total available for use for the year ending March 31, 2020Tablenote 1 Used during the quarter ended June 30, 2019 Year-to-date used at quarter-end Total available for use for the year ending March 31, 2019Tablenote 1 Used during the quarter ended June 30, 2018 Year-to-date used at quarter-end
in thousands of dollars
Tablenote 1

Includes only authorities available for use and granted by Parliament at quarter-end.

Return to tablenote 1 referrer

Vote 1 — Net operating expenditures 430,647 121,622 121,622 409,564 113,579 113,579
Statutory authority — Contribution to employee benefit plans 71,552 17,865 17,865 68,855 15,707 15,707
Total budgetary authorities 502,199 139,487 139,487 478,419 129,286 129,286
Departmental budgetary expenditures by Standard Object (unaudited)
Table summary: This table displays the departmental expenditures by standard object for the fiscal years 2019–2020 and 2018–2019. The row headers provide information by standard object for expenditures and revenues. The column headers provide information in thousands of dollars for planned expenditures for the year ending March 31; expended during the quarter ended June 30; and year to date used at quarter-end.
  Fiscal year 2019–2020 Fiscal year 2018–2019
Planned expenditures for the year ending March 31, 2020 Expended during the quarter ended June 30, 2019 Year-to-date used at quarter-end Planned expenditures for the year ending March 31, 2019 Expended during the quarter ended June 30, 2018 Year-to-date used at quarter-end
in thousands of dollars
Expenditures:
(01) Personnel 540,787 137,419 137,419 512,332 129,600 129,600
(02) Transportation and communications 15,413 3,318 3,318 16,557 2,369 2,369
(03) Information 7,559 1,191 1,191 7,198 933 933
(04) Professional and special services 33,048 5,539 5,539 29,945 4,941 4,941
(05) Rentals 10,676 5,343 5,343 12,207 4,468 4,468
(06) Repair and maintenance 560 97 97 1,241 128 128
(07) Utilities, materials and supplies 1,845 134 134 2,589 188 188
(08) Acquisition of land, buildings and works 516 - - 172 7 7
(09) Acquisition of machinery and equipment 11,635 797 797 10,419 2,822 2,822
(10) Transfer payments 100 - - 100 - -
(12) Other subsidies and payments 60 272 272 5,659 1,177 1,177
Total gross budgetary expenditures 622,199 154,110 154,110 598,419 146,633 146,633
Less revenues netted against expenditures:
Revenues 120,000 14,623 14,623 120,000 17,347 17,347
Total revenues netted against expenditures 120,000 14,623 14,623 120,000 17,347 17,347
Total net budgetary expenditures 502,199 139,487 139,487 478,419 129,286 129,286

Retail Trade Survey (Monthly): CVs for Total sales by geography - June 2019

CVs for Total sales by geography - June 2019
Table summary
This table displays the results of Annual Retail Trade Survey: CVs for Total sales by geography - June 2019. The information is grouped by Geography (appearing as row headers), Month and Percent (appearing as column headers).
Geography Month
201906
Percent
Canada 0.6
Newfoundland and Labrador 1.4
Prince Edward Island 0.8
Nova Scotia 1.5
New Brunswick 1.7
Quebec 1.1
Ontario 1.3
Manitoba 1.1
Saskatchewan 1.6
Alberta 0.8
British Columbia 1.2
Yukon Territory 1.1
Northwest Territories 0.1
Nunavut 1.1

Canadian Vital Statistics Deaths Database (CVSD) linked to Discharge Abstract Database (DAD) National Ambulatory Care Reporting System (NACRS) and Ontario Mental Health Reporting System (OMHRS)

Canadian Vital Statistics Deaths Database (2008-2017) linked to Discharge Abstract Database (2004/05-2017/18), National Ambulatory Care Reporting System (2004/05-2017/18), and Ontario Mental Health Reporting System (2006/07-2017/18)

The objective of this project was to create a linked dataset that can be used to examine a national cohort (save Quebec) of persons who died (for any age group of interest) in relation to the characteristics and intensity of end-of-life care and to identify patient, disease and healthcare factors associated with variations in care intensity and location of death.

To achieve this objective, death records in the Canadian Vital Statistics Death Database (CVSD) from 2008 to 2017 were linked to patient records in the Discharge Abstract Database (DAD) and the National Ambulatory Care Reporting System (NACRS) from 2004/2005 to 2017/2018 and the Ontario Mental Health Reporting System (OMHRS) from 2006/2007 to 2017/2018. Statistics Canada does not have Quebec hospitalization data as part of its data holdings and thus hospitalizations that occurred in the province of Quebec are not included in the linked datasets. Statistics Canada also does not have death data for decedents in the Yukon Territories for death year 2017.

The Data

Canadian Vital Statistics Death Database

The Canadian Vital Statistics Death Database (CVSD) is a census of all deaths occurring in Canada each year. Deaths are reported by the provincial and territorial Vital Statistics Registries to Statistics Canada; the information provided includes demographic and cause of death information. Cause-of-death information is coded using the version of the International Classification of Diseases (ICD) in effect at the time of death. Records eligible for record linkage were deaths that occurred from January 1, 2008 through December 31, 2017, excluding Yukon for 2017.

In addition to the variables from the CVSD, the file includes variables from the Postal Code Conversion File+ (PCCF+) for each linked record. The PCCF+ was generated using the CVSD variable DEA_Q150 (usual residence of the deceased: postal code).

Discharge Abstract Database

The Discharge Abstract Database (DAD) includes administrative, clinical and demographic information on hospital discharges (including in-hospital deaths, sign-outs and transfers) from all provinces and territories, except Quebec. Over time, the DAD has also been used to capture data on day surgery, long-term care, rehabilitation and other types of care. DAD data for fiscal years 2004/2005 to 2017/2018 were included in the linkage.

In the DAD, jurisdiction-specific instructions for collection of data elements evolve over time. Collection of each data element may be mandatory, mandatory if applicable, optional or not applicable. Collection requirements can vary by jurisdiction and by data year. Researchers will find the listings of DAD data elements under the heading “Data Elements” at the DAD Metadata website. The documents on the website include information on mandatory versus optional collection status for each data element by jurisdiction, which is key to understanding coverage of data elements in the DAD.

National Ambulatory Care Reporting System

The National Ambulatory Care Reporting System (NACRS) contains data for hospital-based and community-based ambulatory care including day surgery, outpatient and community-based clinics, and emergency departments. Client visit data are collected at time of service in participating facilities from several jurisdictions. NACRS data for fiscal years 2004/2005 to 2017/2018 were included in the linkage.

For details on the provincial data coverage, please refer to the Data Quality Documentation, available under the “Data Quality” section of the NACRS Metadata website.

In NACRS, jurisdiction-specific instructions for collection of data elements evolve over time. Similar to DAD, collection of each data element may be mandatory, mandatory if applicable, optional or not applicable. Collection requirements can vary by jurisdiction and by data year.

Researchers will find the listings of NACRS data elements under the “Data Elements” section of the NACRS Metadata website. The documents on the website include information on mandatory versus optional collection status for each data element by jurisdiction, which is key to understanding coverage of data elements in NACRS.

Ontario Mental Health Reporting System

The Ontario Mental Health Reporting System (OMHRS) contains data for all individuals receiving adult mental health services in Ontario, in addition to some individuals receiving services in youth inpatient beds and selected facilities in other provinces starting in fiscal year 2006/07. Information regarding mental and physical health, social supports and service use, care planning, outcome measurement, quality improvement, and case-mix funding applications are all part of the OMHRS. For this record linkage, the OMHRS files covering the fiscal years from 2006/07 to 2017/18 were linked to the CVSD. Researchers will find the listings of OMHRS data elements under the heading Data elements at the OMHRS Metadata website.

File structure, layout

A single cohort file was produced of all the individual CVSD records between 2008 through 2017, including those that linked and those that did not link to the DAD, NACRS or OMHRS. A random, unique identifier (variable name: STC_ID) was generated for each record on the CVSD. Each record with a valid postal code has additional information added from the PCCF+. Names and other personal identifiers have been removed from the file.

Separate output files were created for each year of the DAD and for each year of the NACRS. A single cumulative file was created for OMHRS. Only records that linked to the CVSD are included in these outcome files. Since the DAD, NACRS and OMHRS are transactional files, the STC_ID from the CVSD cohort file was included on all records to identify those individuals with multiple transactions within a dataset and across datasets. Merging the STC_ID across datasets (i.e. CVSD to DAD, NACRS and OMHRS) will allow the larger picture of health interventions for an individual to be analysed.

Researchers can choose to use the outcome files as event-based (each row of data represents a hospitalization) or person-based (each row of data represents an individual). In order to use a file as a person-based file, the researcher must transform the data to include all hospital information for one person as one record (one row on the data file).

Restrictions

The linked data should not be used to produce official mortality statistics. Official counts and rates of mortality are available on the Statistics Canada website or can be generated by requesting use of the Canadian Vital Statistics Death Database which is accessible through the RDC or by requesting a custom tabulation from Statistics Canada (statcan.hd-ds.statcan@statcan.gc.ca).

The linked data cannot be used to produce statistics related to institutions and any outputs at the institution level will be restricted as per the vetting rules.

Institution information can be used as a method to generate other information (e.g., the postal code of the institution can be used to determine distance to a care facility) but cannot be used as an outcome of interest.

Date modified: