Eh Sayers Episode 18 - Why Food Inflation Is Such A Hard Nut To Crack

Release date: May 8, 2024

Catalogue number: 45200003
ISSN: 2816-2250

Eh Sayers - Why Food Inflation Is Such A Hard Nut To Crack

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Are you feeling like it's a little bit harder to bring home the bacon... from the grocery store? The latest data indicate that food prices have mostly stabilized... but why does it feel like the cost of feeding your family is still going up? Today, we're talking food inflation with StatCan's resident smart cookie Taylor Mitchell.

Host

Tegan Bridge

Guest

Taylor Mitchell

Listen to audio

Eh Sayers Episode 18 - Why Food Inflation Is Such A Hard Nut To Crack - Transcript

Tegan: Welcome to Eh Sayers, a podcast from Statistics Canada, where we meet the people behind the data and explore the stories behind the numbers. I'm your host, Tegan Bridge.

Let's talk about food. More specifically, let's talk about the price of food. My family likes to cook our own meals, and I used to be really glad about it because it meant that we were saving money by not going out to eat... But... have you seen what groceries cost nowadays? What happened?

We did an episode talking about inflation way back, but I think it's time we did another one, and this time, we're talking turkey. [Pause] Geddit? Because we're talking about food.

So welcome back Taylor.

Taylor: Thanks so much for having me.

Tegan: And remind us who you are?

Taylor: My name is Taylor Mitchell. I am the Program Manager for Analysis, Dissemination, and Communications for the Consumer Price Index here at Statistics Canada.

Tegan: So we're here to talk about food prices. And this is an actual anecdote from my actual life. My family budgets 50 percent more for our groceries than we did a few years ago.

Taylor: 50%?

Tegan: 50%.

Taylor: Okay.

Tegan: But the latest data are saying that food prices have stabilized. Well, not for me, they haven't. Can you make this make sense?

Taylor: So you're telling me that you budget 50 percent more.

Do you actually spend 50 percent more? Because I know that when I go to the grocery store, it can vary a lot from week to week. It can vary in terms of what I'm buying. It can vary in terms of whether, you know, I walked into a sale that maybe I wasn't expecting. It can vary in terms of the time of year because, you know, certain fruits and vegetables will be in season or will be out of season.

So I guess my question is, you know, just because you're expecting to spend more, are you actually spending that much more?

Tegan: You know, well, it's a little bit more complicated. Some months do spend more, some months do spend less. I would say overall it has increased, but I know for sure the budgeting has increased.

Taylor: Prices have definitely increased, so you're, you're not alone in feeling the pinch there

I always say I'm somebody that works on price data. I look at price data all day long at work, and yet I'm still a person that goes to the grocery store and I feel, I think the same, the same frustration that everybody else feels because it feels like prices have gone up so much in a relatively short amount of time. But with the CPI, we are looking at a specific time horizon. We're looking at the last 12 months.

So when we're talking about food inflation, we're talking about, uh, how Food prices or grocery prices have changed between March of 2024 and March of 2023, which is actually only 1.9%. But that feels pretty inconsistent with most of our experiences of the grocery store. Um, and that's because we're just looking at that 12 month period. But if we extend that period back a little bit, and we look at, let's say, from the beginning of the pandemic until now, uh, prices for groceries have actually risen about 23%. And that's going to be a little bit more, a little bit less, depending on how you spend your money. Someone that's a vegetarian is certainly going to be facing a different level of grocery inflation than somebody that eats a lot of meat.

If you're eating a lot of fish, it might be a little bit less because fish prices are only up about 10 percent during that time period. But it's other things like fresh fruit, we've seen higher grocery inflation for fruits than for vegetables. Bakery products are up a little bit so it comes down to preferences and consumer behavior as well.

Tegan: So maybe it's, I know you're not a psychologist, but maybe it's more of a psychology thing. I'm, I'm still left reeling then from these price increases and they haven't gone down and I'm still thinking, wow, everything's so expensive.

Taylor: Well, let's put it this way. I think that our perceptions of inflation are often shaped by things that we buy all the time. And we buy groceries all the time because we need to eat.

Tegan: So are they going to go back down eventually?

Taylor: Uh, well, historically speaking, food prices have not really meaningfully come down over time. Um, and that doesn't mean that you might not have a month where prices do fall a little bit. Food is very seasonal and often there are kind of temporary supply shocks.

You know, we've all, I'm sure we all remember, uh, a romaine lettuce situation where prices skyrocketed and then came back down. But for the most part, as a, as a longer term trend, prices typically have not historically fallen for food.

Tegan: So it's more of a new normal.

Taylor: It's, it's probably more of a level shift. I will note that, uh, you know, the COVID 19 pandemic, it really is a unique set of circumstances. And, uh, we're still seeing a situation where there are some still, there's still some supply chain considerations. It's really not clear how that's going to look moving forward. But historically speaking, um, prices tend to move upward for food.

Tegan: How do you know for a fact that your data are accurate? Are we shopping at the same grocery store?

Taylor: So we actually see food as a real point of strength for the CPI program. And that's because we have access to, to transaction data, which is collected from the point of sale. So You know, I go to the grocery store. I buy my groceries. The data from that transaction is aggregated. So it includes exactly what I paid, you know, whether I got something on sale, whether I paid full price. An aggregated form of that data is sent to Statistics Canada. And so our prices are actually based off of millions of grocery transactions from major grocery retailers, including all their subsidiaries. So the, the lower cost subsidiaries and the, the, the higher end chains, we receive those data and those form the basis for the majority of the food prices that we collect. So it really is the gold standard. It's, it's the best data that are available. It's, it's what Canadians are paying.

Tegan: Would it be possible, conceivably, to measure inflation in a way that's better, faster, and more accurate than what we're doing right now?

Taylor: Better, faster, and more accurate? As far as food goes, this method really is the gold standard. What we want to measure when we are looking at price change over time, we want to measure the prices that Canadians are actually paying.

And that in some cases might be different than what's on the shelf at the store. And so because we have this transaction data, we are capturing what Canadians are actually paying and we are receiving that data in a very timely fashion. So this is really a point of strength for us. And uh, and it's, it's, um, it's a situation where we really don't see much, much room for improvement because we're very satisfied that this is the best price data for food in Canada.

Tegan: What drives food inflation?

Taylor: All kinds of things. Um, so over the past, over the past few years, we've, we've seen a number of factors really influencing food inflation. Um, we've seen weather factors. We've seen droughts and we've seen rain. We've seen that impacting supply and shortening the growing season. In some cases, we've seen Russia's invasion of Ukraine, which had a very noticeable impact, especially if you're someone that likes to buy bread or pasta or anything that that contains wheat. You know, that's that's the world's breadbasket and we're still, we're still impacted by the invasion of Ukraine. It's resulted in higher prices for inputs along the supply chain. And we have trade embargoes with Russia that have reduced supplies for, for some other inputs.

Tegan: Are there any common misconceptions about food inflation that you'd like a chance, take the chance to address?

Taylor: So alongside the CPI, we publish average retail prices for a variety of food products, and we see these average food prices as being really a complimentary tool to the CPI. But one thing that they don't do is, is tell us how prices have changed over time. The CPI, it tracks the exact same jar of peanut butter every month from the exact same grocery store. And we look at how that price has changed over time.

Average retail prices, they look at what Canadians are actually purchasing. So, for instance, if Canadians are buying brand name peanut butter in January, but in February, they decide to buy, you know, the house brand peanut butter, you know, maybe the house brand's gone on sale, the average retail price table might actually show a lower price in February than it did in January because that consumer preference has changed. But that's not really a price change. That's it's not really telling us anything about inflation. So when it comes to looking at price change over time, we always like to remind our users to use the CPI first and foremost, and that other tables like the average retail prices table are are complimentary tools and they're not a replacement.

Tegan: So comparing with the CPI is comparing apples to apples and using the average price is apples to oranges.

Taylor: Exactly. It's, uh, it might show you a price change, but not what we call a pure price change. And it hasn't, it's not accounting for, for things like quality changes as well, which is another, another thing that the CPI holds constant. Because as anyone that's bought groceries lately knows, uh, you know, shrinkflation is a real, a real topic of conversation.

And, and the CPI holds quantities for products standard, so if you know that jar of peanut butter has gotten smaller in size over the years, all else equal, that's going to be considered a price increase for the CPI.

Tegan: Gotcha. I understand that.

If someone would like to learn more about food inflation, the CPI, and how StatCan measures it, where should they go?

Taylor: We've got so many great tools, uh, for Canadians to explore inflation and learn more about, you know, inflation more broadly, but food inflation specifically. We have a data visualization tool, the Consumer Price Index Data Visualization Tool. It has a neat little subtool called Price Trends 1914 to Today. Uh, consumers can explore food inflation for, for all different types of commodities, going down to a pretty low level of detail. Explore how prices have changed over time. We also have a new, a new hub, the Food Price Data Hub, which contains, you know, a multitude of information all about food prices, uh, including CPI data, including average retail price data uh, and it also includes information along the supply chain, so Canadians can see how prices are, are changing really from farm to fork.

Tegan: You've been listening to Eh Sayers. Thank you to our guest, Taylor Mitchell.

You can subscribe to this show wherever you get your podcasts. There, you can also find the French version of our show, called Hé-coutez bien! If you liked this show, please rate, review, and subscribe. And thanks for listening!

Asian Heritage Month 2024... By the Numbers

Asian Heritage Month 2024... By the Numbers

Ethnic Origins

  • According to the 2021 Census, 7,013,835 people in Canada reported having Asian origins, representing 19.3% of the population.
  • The top three Asian origins reported in 2021 were Chinese (about 1.7 million people), Indian (India) (approximately 1.3 million) and Filipino (925,490).

Sources:

Racialized Groups

  • The racialized groups with a high proportion of people of Asian origins are Korean, Chinese, Japanese, Filipino, Southeast Asian, West Asian and South Asian populations.
  • Over a 20-year period (from 2001 to 2021), West Asian (214.1%) and Filipino (207.1%) populations grew at significantly higher rates compared with other Asian population groups, such as the South Asian (154.0%), Korean (114.6%), Southeast Asian (87.9%), Chinese (59.9%) and Japanese (42.4%) groups. 
  • The majority (over 60%) of Asian groups are first-generation immigrants.  
  • Because of a distinct immigration history, over one-third (34.2%) of Japanese people have been in Canada for three or more generations.

Sources:

High Educational Attainment & Professional Occupations

  • Many Asian population groups have high educational attainment rates. Working-age (aged 25 to 64) Korean (60.5%), Chinese (56.3%), South Asian (55.2%), West Asian (52.9%), Japanese (48.2%) and Filipino (45.5%) populations have attained a bachelor’s degree or higher at rates above the national average (32.9%) in 2021. 
  • Southeast Asians (30.5%) were the only Asian group that obtained a bachelor’s degree at a lower rate compared with the total population.
  • Largely as a result of higher educational credentials, many Asian populations held higher-paying professional jobs among the working-age population. South Asian and Chinese workers were well represented among engineers, computing professionals and doctors. The working-age West Asian population was also highly represented among engineers and doctors.

Sources:

Labour Force Participation, Self-employment, & Income

  • In the first three months of 2024, Filipino workers aged 25 to 54 had markedly higher employment rates (88.6%) than the total core-age population (83.7%).  
  • Core-age Korean workers experienced the greatest improvement in their employment outcomes from March 2023 to March 2024—their employment rates increased from 80.0% to 84.4%. 
  • West Asian workers aged 25 to 54 were among the groups with the lowest employment rates. Their employment rate declined from 78.4% to 74.0% from March 2023 to March 2024.
  • In the first three months of 2024, the unemployment rates of core-age South Asian (6.7%), Chinese (7.2%) and West Asian (9.0%) workers were higher than the unemployment rate of the total population aged 25 to 54 (5.5%).
  • Many individuals among the Asian population are entrepreneurs. In 2021, all Asian groups aged 25 to 64, except for the Filipino population, had higher self-employment rates (15.2% to 24.0%) compared with the total working-age population (14.9%).
  • As in the case for the total population, the poverty rate for all Asian groups also declined from 2015 to 2020.
  •  In 2020, the Filipino population (3.9%) had a significantly lower poverty rate than the non-racialized population (6.1%), while West Asian (13.4%), Korean (13.4%), Chinese (12.2%), Southeast Asian (9.3%), Japanese (7.3%) and South Asian (7.2%) populations had higher poverty rates compared with the non-racialized population.

Sources:

Notice of release of the Canadian Research and Development Classification (CRDC) 2020 Version 2.0

Release date:  April 30, 2024 (Previous notice)

Revision of CRDC 2020

CRDC 2020 Version 2.0 includes changes for Field of Research (FOR) Classification only. Changes were maintained at the subclass (4 digit) level for this round, as a more widespread changes can be expected in the next revision. The essential of the scope changes were related to splitting off existing subclasses (fields) to accommodate new subclasses. 8 new subclasses or fields were added.

The Generic Statistical Information Model (GSIM) has been used for this revision to identify the types of changes made to the classification: real changes and virtual changes. Real changes are those affecting the scope of the existing classification items or categories, whether or not accompanied by changes in the title, definition and/or the coding. Virtual changes are those made in coding, titles and/or definitions, while the meaning or scope of the classification item remains the same.

Real changes include the addition of the following new subclasses representing fields of research in:

  • Molecular biophysics
  • Mechanical engineering for energy systems (except renewal energy)
  • Mechanical engineering for renewable energy systems
  • Clinical chemistry
  • Black studies
  • Indigenous studies
  • Quebec history
  • Translation studies

Virtual changes include:

  • Identification of "metaverse" in the title of subclass "Virtual and augmented reality, metaverse and related simulations";
  • Identification of "accessibility and critical disability studies" in the definition of subclass "Disability studies";
  • "Indigenous performing arts" was renamed to "Indigenous arts".

For more information on the Canadian Research and Development Classification (CRDC) 2020 Version 2.0, please visit: Canadian Research and Development Classification (CRDC) 2020 Version 2.0

For questions related to the Canadian Research and Development Classification (CRDC) 2020 Version 2.0, please send an email to: statcan.crdc-ccrd.statcan@statcan.gc.ca.

Eh Sayers Episode 17 - It's 8pm... Do You Know What Your Kids Are Googling?

Release date: April 12, 2024

Catalogue number: 45200003
ISSN: 2816-2250

It's 8pm... Do You Know What Your Kids Are Googling?

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It's 8pm... Do You Know What Your Kids Are Googling? graphic 1

It's 8pm... Do You Know What Your Kids Are Googling? graphic 1

StatCan released new analysis into the online culture our kids are growing up in, and it’s far from the best of all possible worlds: misinformation, bullying, violence… and worse.

Analyst Rachel Tsitomeneas joins us to dive into the findings.

Host

Tegan Bridge

Guest

Rachel Tsitomeneas

Listen to audio

Eh Sayers Episode 17 - It's 8pm... Do You Know What Your Kids Are Googling? - Transcript

Tegan: Welcome to Eh Sayers, a podcast from Statistics Canada, where we meet the people behind the data and explore the stories behind the numbers. I'm your host, Tegan Bridge.

Listen, I'm not going to lie. I'm really glad that the Internet was a different place when I was a kid. I remember using online message boards: I was part of a community that talked about video games when I was a pre-teen. That was a kind of proto-social media, I suppose, but we didn't have smartphones. My first cell phone was a flip phone that lived in my backpack and was usually dead because it cost 15 cents to send one text message.

The Internet is not the same now as it used to be, and, I think it's an important point, even two people using the Internet at the same time, they're experiencing two different Internets: the sites you choose to visit, but even the same site might display different information to two different users: algorithms guessing what you want to see, what you might want to click on, what you might want to buy. Your Internet is not my Internet, and the Internet of today is definitely not the Internet of yesteryear.

StatCan recently released new analysis on the online environment and cyberaggression among young people. Joining us in the studio is that article's author.

Rachel: My name is Rachel Tsitomeneas and I am an analyst with Statistics Canada in the Center for Social Data Insights and Innovation.

Tegan: Are young people being exposed to more, shall we say, concerning content online compared to the average user?

Rachel: So, based on data from the 2022 Canadian Internet Use Survey, more than 8 in 10 Canadians who were age 15 to 24 saw information online in the year prior to the survey that they suspected to be false, which is considerably higher than the national average of 70%.

And misinformation can be as simple as giving somebody a wrong time or a date for a party, or it can go as far as becoming disinformation where it's intentionally weaponized and intends to mislead people and purposefully misstates facts.

And young people are seeing this more often, but they're also not as concerned about it as the rest of the population, which is quite interesting.

Tegan: If you're interested in misinformation, we did an entire episode about that called "A little less misinformation a little more true facts, please," but it isn't just misinformation that young people are seeing online.

Rachel: In the numbers that I have seen and in the research that I have recently done, I have found that young people are, in fact, seeing a lot more information and content that may incite hate or violence online than the rest of the population.

Tegan: This type of content might be things like terrorist content or violence towards ethnic groups. And young Canadians were more likely than any age group to see this content online: 71% compared to the national average of 49%.

People bring their whole selves online for better or worse, the good and the bad. What kind of aggressive behaviours do we see online?

Rachel: Aggressive behavior online definitely exists on a continuum: it starts with something as simple as bullying, name calling, teasing, and it can escalate all the way to a hate crime, which can be directed at individuals or groups of people. It's a criminal violation, and it's motivated by hate. It's based on race, language, colour, religion, sex, et cetera. And it can be taken that far online. So there's this whole big continuum, and youth, especially, are exposed to this because they're online so much more often than the rest of the population or older generations.

Tegan: So who's being targeted for bullying and who's being targeted for hate crimes? Is that the same population?

Rachel: It definitely is the same population, and what we found in the data, especially from the Uniform Crime Report, is that young people are definitely the most likely to be victims of online hate crime. And they're also the most likely to be the perpetrators of online hate crimes. The median age of victims of cyber related hate crimes was only 32 years old and the median age of cyber related hate crime perpetrators was only 27 years old.

There's some demographic differences in the types of victimization that people are experiencing. So, young women are often the most likely to be, um, bullied online in a sexualized nature, whereas just young people in general are going to be the victims and the perpetrators of hate crimes online.

Tegan: Young people, then, are both the victims of these online crimes, but they're also the ones we think are committing the crimes?

Rachel: Yeah, a lot of young people are being charged or suspected of committing cyber related hate crimes. A large chunk of people that were charged between 2018 and 2022 were younger people, you know, even between the ages of 12 and 17. So, so children were being charged with these crimes, but a very stark contrast in the perpetrators of cyber related hate crimes is between males and females. So, you know, between 2018 and 2022 again, 87% of the total people charged with or suspected of committing these types of crimes online were men or boys.

Tegan: What are some of the challenges in studying online interactions? Things like misinformation, bullying and hate crimes.

Rachel: The hard part about studying these online interactions is that it's so new. The internet, relatively speaking, is so incredibly new, and especially social media. So it's hard for us to figure out ways to, to collect data on these new and evolving, you know, spaces that people interact with each other and interact with media. So it's really hard for us to try and collect data in a way that's going to help us understand what's going on, and we don't really, uh, use a lot of web scraping and data, sciency type collection yet online. And we've relied really heavily on surveys for this type of data collection. The problem with relying on survey data all the time is that there's some limitations with that, as it's all self-reported data.

Tegan:  From the article that I read that was published a few weeks ago, it looked like it was also limited by police reported interactions.

So, the fact that it's police reported, if somebody, you know, calls me a mean word that you only use for women, you know, I'm not going to report that to the police, but that was certainly egregious behavior online.

Rachel: Absolutely. And that's, uh, that's where this continuum comes in again, from bullying to discrimination to hate crimes. People experience these types of things all the time, but when it comes to reporting to the police, there's a lot of limitations that people feel and that people have. They're, they're scared to report. They don't feel that they can trust authorities when they report. And so a lot of these, these instances go unreported. And so the numbers that we have are definitely underrepresenting what's actually happening.

Tegan: Why do these findings matter? Why is this important?

Rachel: These findings matter because we can see who views online hate content, who views and misinformation,  the types of people who are the perpetrators and are the victims of online hate crimes. And then we can better understand where we should be implementing policy and where we should be trying to help these people and provide resources to them or to try and, you know, encourage people to actually report when something like this happens to them.

Tegan: The findings also matter for well-being.

Rachel: So, recently, I actually have done some work that related, uh, hate crime rates and quality of life indicators. And so, what that research found is that, uh, census metropolitan areas with high rates of hate crime were actually associated with lower quality of life indicators, such as self-reported health, self-reported mental health, and knowing your neighbours.

So, I think that that is an interesting avenue that, uh, could definitely be explored more in the future.

Tegan: What's the biggest takeaway for you?

Rachel: Young people are both the victims and the perpetrators of cyber related hate crimes. And I think it really, um, points to the fact that we need to look at this demographic closer, and we need to understand why they are the victims, why they are the perpetrators beyond just that they're on the Internet more.

Tegan: Is there anything that you would have liked to include in this daily article that you weren't able to for whatever reason?

Rachel: I was going to say, I mean, I would have loved to include all the people that didn't report, but of course they didn't report.

I think that what I would have liked to include, but it just simply doesn't exist, is just more information on the types of content that young people are seeing online. So I would have loved to get more into the specifics of what young people thought as harmful or aggressive content online and really dig deeper into what they thought it was and how they experience it.

Tegan: You've been listening to Eh Sayers. Thank you to Rachel Tsitomeneas for taking the time to speak with us.

For more information on this topic, check out the article published in The Daily February 27, 2024, called "Online hate and aggression among young people in Canada."

You can subscribe to this show wherever you get your podcasts. There, you can also find the French version of our show, called Hé-coutez bien! If you liked this show, please rate, review, and subscribe. And thanks for listening!

Sources

The Daily - Online hate and aggression among young people in Canada

Correspondence Table: Canadian Research and Development Classification (CRDC) 2020 Version 1.0 to Canadian Research and Development Classification (CRDC) 2020 Version 2.0

The Generic Statistical Information Model (GSIM) is now used to identify the types of changes made to the classification. Real changes (RC) are those affecting the scope of the existing classification items or categories, whether or not accompanied by changes in the title, definition and/or the coding. Virtual changes (VC) are those made in coding, titles and/or definitions, while the meaning or scope of the classification item remains the same. The "real changes" are the most important ones to note for analysis.

Only Field Of Research (FOR) were subject to changes and are included in the correspondence table for this version of the classification.

Types of changes in the classification, including Codes, Titles and Classification Items (Based on GSIM)

CSV version (CSV, 3.36 KB)
Correspondence Table: Canadian Research and Development Classification (CRDC) 2020 Version 1.0 to Canadian Research and Development Classification (CRDC) 2020 Version 2.0
CRDC 2020 V1.0 Code CRDC 2020 V1.0 Title CRDC 2020 V2.0 Code CRDC 2020 V2.0 Title GSIM Type of Change Notes
RDF1020509 Virtual and augmented reality, and related simulations RDF1020509 Virtual and augmented reality, metaverse and related simulations VC2 - Name Change Title and definition modification.
RDF1030399 Atomic, molecular, and optical physics, n.e.c. RDF1030309 Molecular biophysics RC4.2 - Split off RDF1030399 continues to exist while part of its denotation moves to a new subclass RDF1030309.
RDF1030399 Atomic, molecular, and optical physics, n.e.c. RDF1030399 Atomic, molecular, and optical physics, n.e.c. RC4.2 - Split off RDF1030399 continues to exist while part of its denotation moves to a new subclass RDF1030309.
RDF2049999 Other mechanical engineering, n.e.c. RDF2049912 Mechanical engineering for energy systems (except renewal energy) RC4.2 - Split off RDF2049999 continues to exist while parts of its denotation move into new subclasses RDF2049912 and RDF2049913.
RDF2049999 Other mechanical engineering, n.e.c. RDF2049913 Mechanical engineering for renewable energy systems RC4.2 - Split off RDF2049999 continues to exist while parts of its denotation move into new subclasses RDF2049912 and RDF2049913.
RDF2049999 Other mechanical engineering, n.e.c. RDF2049999 Other mechanical engineering, n.e.c. RC4.2 - Split off RDF2049999 continues to exist while parts of its denotation move into new subclasses RDF2049912 and RDF2049913.
RDF3020299 Clinical sciences, n.e.c. RDF3020234 Clinical chemistry RC4.2 - Split off RDF3020299 continues to exist while part of its denotation moves to a new subclass RDF3020234.
RDF3020299 Clinical sciences, n.e.c. RDF3020299 Clinical sciences, n.e.c. RC4.2 - Split off RDF3020299 continues to exist while part of its denotation moves to a new subclass RDF3020234.
RDF5099902 Disability studies RDF5099902 Disability studies VC2 - Name Change Definition modification.
RDF5099999 All other social sciences, n.e.c. RDF5099905 Black studies RC4.2 - Split off RDF5099999 continues to exist while parts of its denotation move to new subclasses RDF5099905 and RDF5099906.
RDF5099999 All other social sciences, n.e.c. RDF5099906 Indigenous studies RC4.2 - Split off RDF5099999 continues to exist while parts of its denotation move to new subclasses RDF5099905 and RDF5099906.
RDF5099999 All other social sciences, n.e.c. RDF5099999 All other social sciences, n.e.c. RC4.2 - Split off RDF5099999 continues to exist while parts of its denotation move to new subclasses RDF5099905 and RDF5099906.
RDF6010199 Historical studies, n.e.c. RDF6010115 Quebec history RC4.2 - Split off RDF6010199 continues to exist while part of its denotation moves to new subclass RDF6010115.
RDF6010199 Historical studies, n.e.c. RDF6010199 Historical studies, n.e.c. RC4.2 - Split off RDF6010199 continues to exist while part of its denotation moves to new subclass RDF6010115.
RDF6020299 Linguistics, n.e.c. RDF6020211 Translation studies RC4.2 - Split off RDF6020299 continues to exist while part of its denotation moves to new subclass RDF6020211.
RDF6020299 Linguistics, n.e.c. RDF6020299 Linguistics, n.e.c. RC4.2 - Split off RDF6020299 continues to exist while part of its denotation moves to new subclass RDF6020211.
RDF6040601 Indigenous performing arts RDF6040601 Indigenous arts VC2 - Name Change Title and definition modification.

Canadian Research and Development Classification (CRDC) 2020 Version 2.0 – Introduction

Status

This standard was approved as a recommended standard on May 26, 2020.

Table of contents

Overview

The Canadian Research and Development Classification (CRDC) was jointly developed by the federal research granting agencies, including the Canadian Foundation for Innovation (CFI), the Canadian Institutes of Health Research (CIHR), the Natural Sciences and Engineering Research Council of Canada (NSERC), the Social Sciences and Humanities Research Council (SSHRC), and Statistic Canada (STC).

The CRDC is the collective name for a set of three related classifications developed for use in the measurement and analysis of research and experimental development (R&D) undertaken in Canada. The three constituent classifications included in the CRDC are: Type of Activity (TOA), Fields of Research (FOR), and Socio-economic Objective (SEO).

Although research and development as an economic activity can be measured using classifications such as the North American Industry Classification (NAICS) and the North American Product Classification (NAPCS), the CRDC 2020 represents the first in its kind and introduces a new dedicated framework for measuring research and development activities in Canada. The first version was officially named CRDC 2020 Version 1.0, and it is now replaced by CRDC 2020 Version 2.0.

The use of the three constituent classifications in the CRDC ensures that R&D statistics collected are useful to governments, educational institutions, international organisations, scientific, professional or business organisations and enterprises, community groups and private individuals in Canada.

The development of the CRDC by the agencies was undertaken in co-operation or consultation with major academic and research organisations, experts of specific fields and users of research information in Canada, in particular during seminars, direct exchanges and other consultative methods such as a public consultation. This comprehensive consultative process aimed to ensure that the CRDC is widely accepted and used as the national standard classification in Canada, not only in the compilation of R&D statistics, but also in the study of research and development in Canada in general.

In this introduction, we provide a summarized background to the development of the classification; an explanation of the conceptual basis of the CRDC, including the composition, nature, purpose and structure of the CRDC; the use of the CRDC and guidelines for classifying with the CRDC; the definition and scope of R&D; an outline of what constitutes a unit of R&D for data and reporting purposes.

The CRDC largely follows the guidelines prescribed in the Organisation for Economic Co-operation and Development (OECD), "Frascati Manual 2015", Guidelines for collecting and reporting data on research and experimental development.

The CRDC is also very close to the Australian and New Zealand Standard Research Classification (ANZSRC) in terms of their underlying concepts and their usage, although some groupings might be different, therefore, large content of this introduction will be similar to that of the ANZSRC.

Background

Canada's research funding agencies were using a number of different research classifications across their programs. In most cases, these classifications only covered the mandate of a specific agency rather than all sectors of research, had not been updated in many years, were not aligned with international standards, no longer accurately represent today's research landscape, and only partially met the needs of different end-users. In addition, a growing emphasis on interdisciplinary research, increased international collaboration, the rapid evolution of some research fields, and the increased desire for consistent inter-agency reporting are important additional drivers behind the development of the CRDC.

In 2017, the federal research granting agencies jointly started the development of the CRDC, with Statistics Canada serving as the custodian of the new standard and providing its expertise on statistical standards development and maintenance. To learn more about the development process, we refer the users to two document: Development of the Canadian Research and Development Classification - What we heard (from the consultation process) and a working paper on the CRDC (Canadian Research and Development Classification (ISKO Encyclopedia of KO)) published in June 2019. Additionally for this revision, a consultation process (Participate in the consultation for the update of the Canadian Research and Development Classification (CRDC) 2020 V1.0) was launched, and a separate report (Revision of the Canadian Research and Development Classification (CRDC) 2020 Version 1.0 - What We Heard) was released on the Statistics Canada's Consulting Canadians website.

The CRDC provides a number of benefits such as the ability to produce an up-to-date, relevant and conceptually sound classification, a common approach to classifying research (including multi- or interdisciplinary research) across research organizations and governments, and will assist in communication, consistent reporting, identification of gaps and opportunities, stronger collaborations, and optimized support for new and innovative research.

In addition, the CRDC provides a framework which enables comparisons with other classifications used nationally and internationally.

To support international comparisons and rely on a sound conceptual base, the definition, scope and classification of R&D activities contained in CRDC largely follow the guidelines prescribed in the Organisation for Economic Co-operation and Development (OECD), "Frascati Manual 2015", Guidelines for collecting and reporting data on research and experimental development. For users with the intention of using this classification thoroughly, it is recommended to read that manual as well.

CRDC 2020 Version 1.0 was released on October 5, 2020. One of the commitments made by the Agencies after release was to review the CRDC every 2 years for a minor review and every 5 years for a major review. The scope of the review for CRDC 2020 Version 2.0 was designed with Fields of Research (FOR) as the only focus, which means Type of Activity (TOA) and Socio-economic objective (SEO) classifications remained untouched in this current version. More fundamental changes will be explored and applied as necessary within the larger scope of the next revision (in 2025 or later).

Composition, nature and purpose of the CRDC

The three classifications in the Canadian Research and Development Classification (CRDC) are:

  • Type of Activity (TOA);
  • Fields of Research (FOR); and
  • Socio-economic Objective (SEO).

They can be used in official statistics to analyse the nature of R&D and in conjunction with industrial and institutional sector classifications to produce a set of official statistics that support a variety of user interests.

Type of Activity (TOA) Classification

This classification allows R&D activity to be categorized according to the type of research effort, namely basic or fundamental research (which groups pure basic research and strategic basic research other split in the Frascati Manual 2015), applied research and experimental development.

The types of activity are defined as follows:

  • Basic research: refers to experimental and theoretical work undertaken primarily to acquire new knowledge of the underlying foundation of phenomena and observable facts, without any particular application or use in view. It includes pure basic research (i.e., experimental and theoretical work undertaken to acquire new knowledge without looking for long term benefits other than the advancement of knowledge) and strategic basic research (experimental and theoretical work undertaken to acquire new knowledge directed into specified broad areas in the expectation of practical discoveries). It provides the broad base of knowledge necessary for the solution of recognized practical problems.
  • Applied research: refers to original investigation undertaken in order to acquire new knowledge. It is, however, directed primarily towards a specific, practical aim or objective. It is undertaken either to determine possible uses for the findings of basic research or to determine new ways of achieving some specific and predetermined objectives.
  • Experimental development: refers to systematic work, drawing on knowledge gained from research and practical experience and producing additional knowledge, which is directed to producing new products, materials, policies, behaviours or outlooks, or new processes, systems and services or to improving substantially those already produced or processed/installed.

Field of research (FOR) Classification

This piece of the CRDC allows R&D activity to be categorized or classified according to the field of research (FOR); it is the methodology used in the R&D that is being considered.

The categories within this classification include major fields of research based on the knowledge sources, the objects of interest, and the methods and techniques being used.

Only FOR classification has been modified in CRDC 2020 Version 2.0.

Socioeconomic objective (SEO) Classification

This classification allows the categorization of R&D according to the purpose or outcome of the R&D as perceived by the data provider (researcher). It consists of discrete economic, social, technological or scientific domains for identifying the principal purposes of the R&D. The attributes applied to the design of the SEO classification comprise a combination of industries, processes, products, health, education, culture, ethics and other social and environmental aspects of particular interest.

Structure of the CRDC

Type of Activity (TOA) structure

As noted in section 2, the TOA has 3 main categories with no hierarchy between them, although they can be considered a continuum in the R&D process; for basic research to experimental development.

CRDC 2020 Version 2.0 – Type of Activity (TOA)
Level Level name Number of digits (truncated – Full codes are alphanumerical and start with RDT) Count
1 Division 2 3

Field of Research (FOR) structure

The FOR has four hierarchical levels, namely Divisions (at the broadest level), Groups, Classes and Subclasses or Fields (at the lowest level). The Division represents a broad subject area or research discipline and is closely aligned with the 'broad classification' levels (6 in total) as identified in the Frascati Manual 2015, with some adjustments made based on comments and feedback from consultations with experts and general public (See: Comparison between Frascati Manual 2015 – Broad Classification (FOR) and CRDC 2020 Version 2.0 – Division levels (FOR)). Groups are closely aligned with the 'Second-level classification' (42 in total) as also identified in the Frascati Manual 2015, also with few adjustments (See: Comparison between Frascati Manual 2015 – Second level classification (FOR) and CRDC 2020 Version 2.0 – Group levels (FOR)). While classes and fields were added in the CRDC to represent the increasingly detailed dissections of R&D activities in Canada. Divisions, Groups, Classes and Fields are assigned unique 2-digit truncated codes (full codes for all FOR are alphanumerical starting with RDF); 3-digit truncated codes; 5-digit truncated codes and 7-digit truncated codes respectively. The FOR classification in CRDC 2020 version 2.0 has 6 Divisions, 43 Groups, 168 Classes and 1,671 Subclasses or Fields.

Each Division is based on a broad discipline. Groups within each Division are those which share the same broad methodology, knowledge domain and/or perspective as others in the Division. Each Group is a collection of classes. Groups, Classes and Subclasses (Fields) of research are categorized to the Divisions sharing the same methodology rather than the Division they support.

CRDC 2020 Version 2.0 – Field of Research (FOR)
Level Level name Number of digits (truncated - Full codes are alphanumerical and start RDF) Count CRDC 2020 Version 2.0
1 Division 2 6
2 Group 3 43
3 Class 5 168
4 Subclass (Field) 7 1,671
Total n/a n/a 1,888
Example of the hierarchical structure of the FOR
Level Code Title
Division RDF20-21 Engineering and technology
Group RDF203 Electrical engineering, computer engineering, and information engineering
Class RDF20303 Data analytics and signal processing
Subclass (Field) RDF2030302 Artificial intelligence engineering

Socio-Economic objective (SEO) structure

The SEO is a two-level hierarchical classification with Division at the broadest level and Group at the bottom. SEO categories allow the categorization of R&D based on the purpose or outcome of the R&D as perceived by the researchers. The Division in the SEO classification is identified by a 2-digit truncated code and all full codes start with RDS. This level of the SEO classification of the CRDC is closely aligned with the 'Chapters' found in the Nomenclature for the Analysis and Comparison of Scientific Programmes and Budgets (NABS) 2007 (PDF) (See: Comparison between NABS 2007 Chapters (SEO) and CRDC 2020 Version 2.0 – Division levels (SEO)) developed by Eurostat and it can also be linked to the Frascati Manual 2015 which specifically refers to the NABS when exposing on the socioeconomic objectives for R&D.

Groups form the lowest level of the SEO for CRDC 2020 Version 2.0. They were put together by the funding agencies following up the scope of the NABS 2007 and other considerations such as the experience and uses from funding agencies and Statistics Canada collecting that type of information or data. It is already anticipated that more levels might be added in future revisions of the CRDC's SEO, after more consultations and analysis. Groups are assigned a unique 5-digit truncated code and all full codes start with RDS.

The SEO classification has 12 Divisions and 85 Groups. The Groups are more specific in terms of SEO and they are supplemented with illustrative examples which can represent more specific types of objective within the group. These examples can later be used to create additional levels of SEO.

Each Division is based on a broad research objective. Groups within each Division are those which are aligned towards the same objective as the Division. Each Group is a collection of related research objectives. Groups are categorized to the Divisions with which they are most closely aligned.

CRDC 2020 Version 2.0 – Socio-Economic Objective (SEO)
Level Level name Number of digits (truncated - Full codes are alphanumerical and start with RDS) Count
1 Division 3 12
2 Group  5 85
Example of the hierarchical structure of the SEO:
Level Code Title
Division RDS111 Political and social systems, structures and processes
Group RDS11110 Social justice

Summary of changes from CRDC 2020 Version 1.0 to CRDC 2020 Version 2.0

CRDC 2020 Version 2.0 includes changes for Field of Research (FOR) Classification only. Changes were maintained at the subclass (4 digit) level for this round, as a more widespread changes can be expected in the next revision. The essential of the scope changes were related to splitting off existing subclasses (fields) to accommodate new subclasses. 8 new subclasses or fields were added.

The Generic Statistical Information Model (GSIM) is used to identify the types of changes made to the classification: real changes and virtual changes. Real changes are those affecting the scope of the existing classification items or categories, whether or not accompanied by changes in the title, definition and/or the coding. Virtual changes are those made in coding, titles and/or definitions, while the meaning or scope of the classification item remains the same. Real changes are the most important ones for analysis and tracking changes over time.

Combination of classification items

No combination of classifications items occurs in this revision.

Decomposition of classification items

Among the type of decomposition classification items in the GSIM, only split offs were registered. A split occurs when a classification item continues to exist, while part of its denotation moves to another (emerging) classification item. The following emerging subclasses or fields of research were added in CRDC 2020 Version 2.0:

Subclasses or fields of research were added in CRDC 2020 Version 2.0
Level Code Parent Title
Subclass (Field) RDF1030309 RDF10303 Molecular biophysics
Subclass (Field) RDF2049912 RDF20499 Mechanical engineering for energy systems (except renewal energy)
Subclass (Field) RDF2049913 RDF20499 Mechanical engineering for renewable energy systems
Subclass (Field) RDF3020234 RDF30202 Clinical chemistry
Subclass (Field) RDF5099905 RDF50999 Black studies
Subclass (Field) RDF5099906 RDF50999 Indigenous studies
Subclass (Field) RDF6010115 RDF60101 Quebec history
Subclass (Field) RDF6020211 RDF60202 Translation studies

Virtual Changes

These changes are made without changing the scope of the existing classification items, though they help clarify where a number of fields of research should be classified. In CRDC 2020 Version 2.0, they include:

  • Identification of 'metaverse' in the title of subclass RDF1020509-Virtual and augmented reality, metaverse and related simulations;
  • Identification of 'accessibility and critical disability studies' in the definition of subclass RDF5099902-Disability studies;
  • Subclass RDF6040601-Indigenous performing arts was renamed to Indigenous arts.
CRDC 2020 Version 2.0 – Field of Research (FOR) - Level count after changes
Level Level name Number of digits (truncated - Full codes are alphanumerical and start RDF) Count CRDC 2020 Version 1.0 Count CRDC 2020 Version 2.0
1 Division 2 6 6
2 Group 3 43 43
3 Class 5 168 168
4 Subclass (Field) 7 1,663 1,671
Total n/a n/a 1,880 1,888

Use of the CRDC

The CRDC provides a three-way matrix of classification. Each R&D activity can be classified by Type of Activity (TOA), Fields of Research (FOR) and Socio-economic Objective (SEO).

The CRDC provides a significant degree of flexibility in meeting the needs of a wide variety of users. The hierarchical structure of both the FOR and SEO classifications enables them to be applied to particular purposes at various levels. The CRDC also helps classify multi-disciplinary research, where several disparate areas of the FOR are usually brought together to address one area, or closely related areas of the SEO.

The complexity of issues addressed by R&D is such that questions of public policy often arise in a manner which cannot be readily seen in advance. The detail available in both the FOR and SEO classifications would be sufficient to facilitate the provision of statistics that can be used in a variety of contexts. For example, areas of key technological significance could generally be assessed using an aggregate of appropriate FOR classes and subclasses (fields). The use of the CRDC for R&D surveys minimises the need for separate one-off R&D surveys aimed at narrow areas.

Guidelines for classifying with the CRDC

Classifying by type of activity (TOA)

Where possible, a research project or research program should be allocated to a single type of activity (basic research, applied research or experimental development). If the project or program is large and involves multiple types of activity, then each relevant activity category should be attributed a proportion of resources relative to the project's or research program's total R&D expenditure.

Classifying by field of research (FOR)

The research should first be considered in its broadest sense and in terms of the discipline that the research relates. The research is to be allocated to a FOR in a hierarchical manner. This is achieved by:

  • first determining the most relevant division in which the largest component of the R&D is being performed; then
  • determining the most relevant group within that division; then
  • determining the most relevant class within that group; and then
  • determining the most relevant subclass or field within that class.

Many R&D projects will be a homogenous body of work in a specific field. These are more straightforward to categorize. However, the emergence of new interdisciplinary and multidisciplinary fields of research is a feature of the modern R&D environment. The categorization of such fields within a hierarchical and exclusive classification system can pose difficulties for users of the FOR. The use of multiple fields to classify a research project ensures that this research is accommodated within the classification structure.

For example, to classify multidisciplinary research, granting agencies in Canada will each identify how they will classify them during their implementation of the CRDC. One could for instance collect 3 to 5 fields of research (FOR) to describe a particular research project.

If the research is sufficiently large or complex then multiple fields should be selected and attributed with a proportion of resources relative to the total expenditure of the R&D. If the disaggregation is difficult, consideration of relative importance may indicate a primary objective only.

Where a defined field cannot be identified within a class, the 'not elsewhere classified (n.e.c.)' category at the field level is to be used.

Classifying by socioeconomic objective (SEO)

The research should first be considered in its broadest sense and in terms of the dominant beneficiary of the research output. The research is to be allocated to an SEO in a hierarchical manner. This is achieved by:

  • first determining the most relevant division corresponding to the largest component of the R&D being performed and the socioeconomic objective which covers that research and experimental development (R&D) activity; then
  • determining the most relevant group or objective within that division;
  • illustrative examples can be used to determine the most relevant objective within the group.

The appropriate SEO should reflect the industry, process, product, health, education or other social and environmental aspect that R&D activity aims to impact, improve or measure. The appropriate SEO may reflect the aspirations of the researchers and it may help to understand the goals of the research.

Many R&D projects will be a homogenous body of work directed towards a specific objective. These are more straightforward to categorize. However, if the R&D is sufficiently large or complex then multiple fields should be selected and attributed with a proportion of resources relative to the total expenditure of the R&D. If the disaggregation is difficult, consideration of relative importance may indicate a primary objective only.

Where a defined objective cannot be identified within a group, the 'not elsewhere classified (n.e.c.)' or residual category at the objective level is to be used.

In terms of objectives leading towards 'expanding knowledge', for this first version of the CRDC, it was decided to include them in residual categories (n.e.c.). 'Expanding Knowledge' is for the categorization of R&D which does not have an identifiable socio-economic objective. This is usually the case for basic research (as defined in the Type of Activity classification). Applied research and experimental development, by definition, have an identified socio-economic objective and therefore should not be categorized as 'expanding knowledge'.

Definition of R&D

Research and Development (R&D) is defined according to the OECD standard (Frascati Manual 2015) as comprising creative work undertaken on a systematic basis in order to increase the stock of knowledge, including knowledge of human, culture, society and environment, and the use of this stock of knowledge to devise new applications.

An R&D activity is characterized by originality. It has investigation as a primary objective, the outcome of which is new knowledge, with or without a specific practical application, or new or improved materials, products, devices, processes or services. R&D ends when work is no longer primarily investigative.

Scope of R&D

As indicated in the Frascati Manual 2015 and as experience has shown, there are difficulties in delineating the point which clearly separates the culmination of R&D investigative work and the beginning of the implementation phase of the innovations or recommendations resulting from R&D. Errors at this point are particularly significant because, although R&D programmes require large outlays of resources, the costs of implementing innovations or recommendations resulting from R&D may also be as high, or higher, in many instances.

There is also a wide range of scientific and related activities that are not R&D, but that are closely linked to R&D in terms of organisation, resource allocation, institutional affiliation and the use or flow of information. However, activities conducted solely or primarily for the purposes of R&D support are included in R&D.

The activities which do not have clear boundaries with R&D are listed below.

(i) Education and training of personnel and students

Postgraduate research, including supervision of the research, is considered to be R&D. The development of new teaching methods is also regarded as R&D. However, teaching and training students, using established methods and subject knowledge, is excluded.

(ii) Specialised scientific and technical information services

Specialised scientific and technical information services which are undertaken solely in support of R&D are regarded as R&D. Examples of these are scientific data collection, coding, recording, classification, dissemination, translation, analysis and bibliographic services.

These specialised services are excluded if they are undertaken independently and not solely in support of R&D.

(iii) General purpose or routine data collection

Collecting data in support of R&D work is included in R&D.

However, data collection of a general nature is excluded. This is normally carried out by government agencies to record natural, biological, economic, or social phenomena of general public or government interest. Examples are national population censuses, surveys of unemployment, topographical mapping and routine geographical or environmental surveys.

(iv) Maintenance of national and international standards

Routine testing and analysis of materials, components, products, processes, soils, atmospheres, etc. for standard compliance is excluded from R&D.

(v) Feasibility studies

Feasibility studies undertaken in support of R&D are included. However, a feasibility study that involves gathering information about existing conditions, for use in deciding whether or not to implement a project, is excluded, e.g., a study to determine the viability of a petrochemical complex in a particular location.

(vi) Specialized medical care

R&D includes the development of new treatments and procedures, including such developments in conjunction with advanced medical care and examinations usually carried out by university hospitals.

However, routine investigations or normal application of specialized medical knowledge, techniques or equipment are excluded from R&D. Examples of these are pathology, forensic and post-mortem procedures.

(vii) Clinical trials

Phase 1, 2 and 3 clinical trials are included in R&D. Phase 4 clinical trials are excluded from R&D, unless they bring about further scientific or technological advance.

(viii) Patent and licence work

Patent work connected directly with R&D projects is included in R&D. However, commercial, administrative, and legal work associated with patenting, copywriting and licensing, is excluded.

(ix) Policy or program related studies

The boundary between certain policy related studies as described in the Frascati Manual 2015 and R&D is complex. In the Frascati Manual, policy related studies cover activities such as the 'analysis and assessment of existing programmes, continued analysis and monitoring of external phenomena (e.g., defence and security analysis), legislative inquiry concerned with general government departmental policy or operations'. Rigour is required to separate policy related studies that are not R&D from true R&D policy work.

Studies to determine the effects of a specific national policy or program to a particular economic or social condition or social group may have elements of R&D. Routine management studies or efficiency studies are excluded.

(x) Routine software development

Software development is an integral part of many projects which in themselves may have no element of R&D. The software development component of such projects, however, may be classified as R&D if it leads to an advance in the area of computer software.

For a software development to be considered as R&D, its completion must be dependent on a scientific or technological advance, and the aim of the project must be the systematic resolution of a scientific and/or technological uncertainty.

The following are examples of software development which are considered to be R&D:

  • Development of internet technology
  • Research into methods of designing, developing, deploying or maintaining software
  • R&D on software tools or technologies in specialized areas of computing (e.g. image processing, artificial intelligence, character recognition)
  • R&D producing new theorems and algorithms in the field of theoretical computer science

The following are examples of software development which are not considered to be R&D:

  • Routine computer and software maintenance
  • Business application software and information system development using known methods and existing software
  • Adding user functionality to application languages
  • Adaptation of or support for existing software

(xi) Marketing and market studies

Market research and opinion polls are excluded from R&D.

(xii) Mineral exploration

The development of new or vastly improved methods of data acquisition, processing and interpretation of data is included as R&D. Surveying undertaken as an integral part of an R&D project to observe geological phenomena is also regarded as R&D. However, the search for minerals using existing methods is excluded from R&D.

(xiii) Prototypes and pilot plants

The design, construction and testing of prototypes generally falls within the scope of R&D. However, trial production and copying of prototypes are excluded from R&D.

The construction and operation of pilot plants is part of R&D provided that these are used to obtain experience or new data for evaluating hypotheses.

Pilot plants are excluded from R&D as soon as the experimental phase is over or as soon as they are used as normal commercial production units, even if they continue to be described as 'pilot plants'.

If a pilot plant is used for combined operations, the component used for R&D is to be estimated.

(xiv) Other activities

All other activities that are ancillary or consequential to R&D are excluded. Examples of these are interpretative commentary using existing data, forecasting, operations research as contributing to decision making and the use of standard techniques in applied psychology to classify or diagnose human characteristics.

R&D unit or object to be classified

There are some inherent difficulties in formulating a definition of what constitutes a unit of R&D, due to the lack of uniformity in organizational structures and considerable variation in the way organizations allocate resources to R&D activities. From a statistical viewpoint it is desirable that R&D expenditure be reported in the smallest cluster that can be classified to a single TOA and FOR, which for the purposes of this classification is defined to be an R&D unit. The extent to which it is not practicable to provide this detail will reduce the validity and usefulness of the classification, and the resulting R&D statistics.

The most common real world references to R&D activities are Research Program and Research Project. These focal units seldom approximate the idealized R&D unit as outlined above, although they could be regarded as an aggregation of these units.

We refer to the Frascati Manual 2015 for more details about the best way to identify R&D units.

Relationship with other national statistical classifications

The CRDC is the first Canadian research classification designed to be dedicated to R&D and inclusive of all current sectors of research in Canada. While contributing to a greater alignment with international standards, it is comprehensive enough to support a wide range of needs within the Canadian research and development ecosystem.

It might be possible to combine the CRDC and the North American Industry Classification (NAICS) Canada when collecting, analyzing and disseminating R&D data. There are also some approximations to be made with the Classification of instructional programs (CIP) Canada and the North American Product Classification (NAPCS) Canada, although direct comparison should be made with care. In the case of NAPCS Canada for example, it is a transaction and output-based classification which may not be suited to all situations where R&D information needs to be collected and disseminated, for example 'intra-muros R&D'.

Relationship with relevant international standard classifications

The CRDC aligns with international standards to collect and report on research and development, namely with the recommendations from the Organization for Economic Cooperation and Development's (OECD) Frascati Manual 2015, the Nomenclature for the Analysis and Comparison of Scientific Programmes and Budgets (NABS) 2007 and was modeled on the Australian and New Zealand Standard Research Classification (ANZSRC) 2008. Since then the ANZSRC has been revised to Version 2020.

See the comparison tables for fields of research (FOR):

Comparison between Frascati Manual 2015 – Broad Classification (FOR) and CRDC 2020 Version 2.0 – Division levels (FOR)
Frascati Manual 2015 - Broad Classification (FOR) - Code Frascati Manual 2015 - Broad Classification (FOR) - Title CRDC 2020 Version 2.0 – Division levels (FOR) – Code CRDC 2020 Version 2.0 – Division levels (FOR) - Title Explanatory notes
1 Natural sciences RDF10 Natural sciences  
2 Engineering and technology RDF20-21 Engineering and technology  
3 Medical and health sciences RDF30 Medical, health and life sciences Difference in the title with addition of 'and life sciences' in the CRDC.
4 Agricultural and veterinary sciences RDF40 Agricultural and veterinary sciences  
5 Social sciences RDF50 Social sciences  
6 Humanities and the arts RDF60 Humanities and the arts  
Comparison between Frascati Manual 2015 – Second level classification (FOR) and CRDC 2020 Version 2.0 – Group levels (FOR)
Frascati Manual 2015 – Second level classification (FOR) Code Frascati Manual 2015 – Second level classification (FOR) Title CRDC 2020 Version 2.0 – Group levels (FOR) - Code CRDC 2020 Version 2.0 – Group levels (FOR) - Title Explanatory notes
1.1 Mathematics RDF101 Mathematics and statistics Difference in the title with addition of 'statistics' in the CRDC.
1.2 Computer and information sciences RDF102 Computer and information sciences  
1.3 Physical sciences RDF103 Physical sciences  
1.4 Chemical sciences RDF104 Chemical sciences  
1.5 Earth and related environmental sciences RDF105 Earth and related environmental sciences  
1.6 Biological sciences RDF106 Biological sciences  
1.7 Other natural sciences RDF107 Other natural sciences  
2.1 Civil engineering RDF201 Civil engineering, maritime engineering, transport engineering, and mining engineering Difference in the title with addition of 'maritime engineering, transport engineering, and mining engineering' in the CRDC.
2.2 Electrical engineering, electronic engineering, information engineering RDF203 Electrical engineering, computer engineering, and information engineering  
2.3 Mechanical engineering RDF202 Industrial, systems and processes engineering CRDC identifies this category as important for Canada and elevates it at the Frascati second level classification. Though, the category is part of Mechanical engineering in the Frascati Manual 2015.
2.3 Mechanical engineering RDF204 Mechanical engineering  
2.4 Chemical engineering RDF205 Chemical engineering  
2.5 Materials engineering RDF206 Materials engineering and resources engineering Difference in the title with addition of 'resources engineering' in the CRDC.
2.6 Medical engineering RDF207 Medical and biomedical engineering Difference in the title with addition of 'biomedical' in the CRDC.
2.7 Environmental engineering RDF208 Environmental engineering and related engineering Difference in the title with addition of 'and related engineering' in the CRDC.
2.8 Environmental biotechnology RDF209 Environmental biotechnology  
2.9 Industrial biotechnology RDF210 Industrial biotechnology  
2.10 Nano-technology RDF211 Nano-technology  
2.11 Other engineering and technologies RDF212 Other engineering and technologies  
3.1 Basic medicine RDF301 Basic medicine and life sciences Difference in the title with addition of 'and life sciences' in the CRDC.
3.2 Clinical medicine RDF302 Clinical medicine  
3.3 Health sciences RDF303 Health sciences  
3.4 Medical biotechnology RDF304 Medical biotechnology  
3.5 Other medical science RDF305 Other medical sciences  
4.1 Agriculture, forestry, and fisheries RDF401 Agriculture, forestry, and fisheries  
4.2 Animal and dairy science RDF402 Animal and dairy sciences  
4.3 Veterinary science RDF403 Veterinary sciences  
4.4 Agricultural biotechnology RDF404 Agricultural biotechnology and food sciences Difference in the title with addition of 'and food sciences' in the CRDC.
4.5 Other agricultural sciences RDF405 Other agricultural sciences  
5.1 Psychology and cognitive sciences RDF501 Psychology and cognitive sciences  
5.2 Economics and business RDF502 Economics and business administration Difference in the title with addition of 'administration' in the CRDC.
5.3 Education RDF503 Education  
5.4 Sociology RDF504 Sociology and related studies Difference in the title with addition of 'and related studies' in the CRDC.
5.5 Law RDF505 Law and legal practice  
5.6 Political science RDF506 Political science and policy administration Difference in the title with addition of 'and policy administration' in the CRDC.
5.7 Social and economic geography RDF507 Social and economic geography  
5.8 Media and communications RDF508 Media and communications  
5.9 Other social sciences RDF509 Other social sciences  
6.1 History and archaeology RDF601 History, archaeology and related studies Difference in the title with addition of 'and related studies' in the CRDC.
6.2 Languages and literature RDF602 Languages and literature  
6.3 Philosophy, ethics and religion RDF603 Philosophy Difference in the title with the removal of 'ethics and religion' in the CRDC; these words were added in the definition of the category.
6.4 Arts (arts, history of arts, performing arts, music) RDF604 Arts (arts, history of arts, performing arts, music), architecture and design Difference in the title with addition of 'architecture and design' in the CRDC.
6.5 Other humanities RDF605 Other humanities  

See the comparison table for socioeconomic objectives (SEO):

Comparison between NABS 2007 Chapters (SEO) and CRDC 2020 Version 2.0 – Division levels (SEO)
NABS 2007 Chapters (SEO) – Code NABS 2007 Chapters (SEO) – Title CRDC 2020 Version 2.0 – Division levels (SEO) – Code CRDC 2020 Version 2.0 – Division levels (SEO) – Title Explanatory notes
1 Exploration and exploitation of the Earth RDS101 Exploration and exploitation of the earth  
2 Environment RDS102 Environmental protection Difference in the title with addition of 'protection' in the CRDC.
3 Exploration and exploitation of space RDS103 Exploration and exploitation of space  
4 Transport, telecommunication and other infrastructures RDS104 Transport, telecommunication and other infrastructures (including buildings) Difference in the title with addition of 'including buildings' in the CRDC.
5 Energy RDS105 Energy (except prospecting) Difference in the title with addition of 'except prospection' in the CRDC.
6 Industrial production and technology RDS106 Industrial production and technology  
7 Health RDS107 Health  
8 Agriculture RDS108 Agriculture (including fisheries and forestry)  
9 Education RDS109 Education  
10 Culture, recreation, religion and mass media RDS110 Culture, recreation, religion and media Difference in the title with the removal of 'mass' for media in the CRDC.
11 Political and social systems, structures and processes RDS111 Political and social systems, structures and processes  
12 General advancement of knowledge: R&D financed from General University Funds (GUF)     No direct equivalent. This category is spread across different residual categories in the CRDC.
13 General advancement of knowledge: R&D financed from other sources than GUF     This category is spread across different residual categories in the CRDC.
14 Defence RDS112 Defence  

Updates or revisions to the CRDC

An important consideration when developing a statistical classification is the need to build in sufficient robustness to allow for long-term usage. This robustness facilitates meaningful time series analysis of data assigned to that classification. However, there is also a need for the classification to remain contemporary to capture changes happening in the R&D sector and to provide data relevant to users' needs.

In order to achieve a balance between these two competing objectives, Statistics Canada as the custodian of the CRDC, and its close partner funding agencies, intend to undertake minor revisions every year or two, and major revision every five years. In fact, all parties agreed that the first CRDC 2020 version 1.0 will be revised within 2 years of its first release date, and on a five-year cycle after that, with possibility of 'evergreening' for minor changes once a year to reflect the changes in the research fields. This is the first revision of the classification with CRDC 2020 Version 2.0. More revisions will continue in the future according to this approximatively 5-years revision cycle.

Although the CRDC is official once published by Statistics Canada, the dates of its implementation depend entirely on the entities, organizations or individuals who decide to use it. Statistics Canada has its own internal policies on statistical standards and informing users that may influence implementation dates by the Agency's statistical programs.

CRDC products

Correspondences (or concordances) between newest versions and older versions of the CRDC will be provided along with the classification after it revised. This is the first official version of the CRDC, therefore no correspondence table will be released. Other correspondences will be considered for development in the future, including full correspondences between CRDC FOR and OECD's Fields of Science (See: Comparison between Frascati Manual 2015 – Broad Classification (FOR) and CRDC 2020 Version 2.0 – Division levels (FOR) and Comparison between Frascati Manual 2015 – Second level classification (FOR) and CRDC 2020 Version 2.0 – Group levels (FOR)), between CDRC's SEO and the Nomenclature for the Analysis and Comparison of Scientific Programmes and Budgets (NABS) 2007 (See: Comparison between NABS 2007 Chapters (SEO) and CRDC 2020 Version 2.0 – Division levels (SEO)), and potentially develop crosswalks between the CDRC's FOR and SEO, and the North American Industry Classification (NAICS), between the CRDC's FOR and SEO, and the North American Product Classification (NAPCS) Canada, and between the CRDC's FOR and SEO, and the Classification of Instructional Programs (CIP). But these crosswalks might take time to develop and will depend on available resources, as the focus will be the deployment of the CRDC and experiment of its usage across the country for some years after the first release.

Further information

For more information about the CRDC contact Statistics Canada: Contact us

For more information on the Canadian Research and Development Classification (CRDC) 2020 Version 2.0, please visit: Canadian Research and Development Classification (CRDC) 2020 Version 2.0

For questions related to the Canadian Research and Development Classification (CRDC) 2020 Version 2.0, please send an email to: statcan.crdc-ccrd.statcan@statcan.gc.ca.

References

Canadian Research and Development Classification (CRDC) 2020 Version 2.0

Release date: April 30 , 2024

Status

This standard was approved as a recommended standard on May 26, 2020.

CRDC 2020 Version 2.0

The Canadian Research and Development Classification (CRDC) was developed conjointly by the Social Sciences and Humanities Research Council of Canada (SSHRC), the Natural Sciences and Engineering Research Council of Canada (NSERC), the Canada Foundation for Innovation (CFI), the Canadian Institutes of Health Research (CIHR), and Statistics Canada which is the custodian. This shared standard classification, inspired by the Frascati Model 2015 of the Organisation for Economic Co-operation and Development (OECD), will be used by the federal granting agencies and Statistics Canada to collect and disseminate data related to research and development in Canada. The CRDC first official version is the 2020 version 1.0 and it is replaced by this Version 2.0. CRDC 2020 Version 2.0 is composed of 3 main pieces: the type of activity or TOA (with 3 categories), the field of research or FOR (with 1,671 fields at the lowest level) and socioeconomic objective or SEO (with 85 main groups at the lowest level).

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CSV format

Correspondence tables

Invitation to participate in the revision of the Classification of Instructional Programs (CIP) Canada

Opened: April 2024

Introduction

Statistics Canada invites data producers and data users, representatives of educational institutions and professional associations, government bodies at the federal, provincial/territorial, and local levels, educational experts, academics and researchers and all other interested parties to submit proposals for the revision to the Classification of Instructional Programs (CIP) Canada.

Following the decision of the Statistics Canada's Social Standards Steering Committee (SSSC) on January 9, 2024, to institute a permanent consultation process for CIP Canada, proposals for changes may be submitted and reviewed on an ongoing basis. Only a cut-off date for considering proposed changes to be included into a new version of the CIP Canada will be instituted moving forward. For future revisions of the CIP Canada, a cut-off date will be maintained at about one and a half years prior to the release date of the new classification version.

In exceptional circumstances, when a consensus is reached among the data producers and users at Statistics Canada, the classification might be revised before the regular revision cycle of 5-years, as the way of 'evergreening' the standard.

In the context of statistical classifications, evergreening refers to updating the classification and the related reference (index) file on a continuous basis with the objective of maintaining quality, timeliness and relevance. Though, evergreening does not necessarily result in the release of a new version of the classification every year. A decision to release a new version (before the end of the regular 5 years revision cycle) needs to be discussed and assessed by key classification stewards considering potential impacts on data and statistical programs.

Objectives

This consultation aims to gather feedback from users who have already implemented the classification, as well as other interested parties who might want to suggest updates or changes. The principal objective of the consultation is to receive input from classification users to determine if the classification remains relevant and reflective of Canadian postsecondary educational programs. This ensures that quantitative and qualitative information on postsecondary educational programs continues to be reliable, timely and relevant for a wide range of audiences.

Background

The Classification of Instructional Programs (CIP) Canada 2021 is the fourth Canadian version of this classification; others being CIP Canada 2000, 2011 and 2016. The CIP Canada revisions were accomplished through the joint efforts of Statistics Canada and the National Center for Education Statistics (NCES) of the United States Department of Education.

In September 2023, Statistics Canada's Social Standards Steering Committee (SSSC) made the decision to move from a 10-year to a 5-year CIP revision cycle. The next version of the CIP Canada will be in 2027 and will align with the new 5-year U.S. CIP 2025.

Nature and content of proposals

Respondents are invited to provide their comments, feedback, and suggestions on how to improve the CIP Canada. They must outline their rationale for proposed changes.

Respondents may propose virtual (not affecting the meaning of a classification item) and real changes (affecting the meaning of a classification item, whether accompanied by changes in naming and/or coding or not). Examples of real changes are: the creation of new classification items, the combination or decomposition of classification items, as well as the elimination of classification items. A classification item (sometimes referred to as a "class") represents a category at a certain level within a statistical classification structure. It defines the content and the borders of the category, and generally contains a code, title, definition/description, as well as exclusions where necessary. For the CIP Canada, classifications items are: Series (2-digit), Sub-series (4-digit) and Class (6-digit).

Key dates for the CIP Canada 2027 revision process

Here are key dates for the CIP Canada 2027 revision process:

  • Official public consultation period for changes proposed for inclusion in the CIP Canada 2027: Ongoing to the end of June 2024. Beyond the CIP Canada 2027, the cut-off date to incorporate approved changes from proposals into the new classification version will be about a year and a half before the release date of the next version of the CIP based on the 5-year revision cycle.
  • Public notice containing proposals in consideration for changes in the CIP Canada 2027: winter of 2024
  • Public notice containing the final approved proposal for changes in the CIP Canada 2027: spring/summer 2025
  • Public release of the CIP Canada 2027 Version 1.0: late 2027/early 2028

The next revised version of CIP Canada will be called CIP Canada 2027 Version 1.0.

Individuals and organizations wishing to submit proposals for changes in CIP Canada may do so at any time, in accordance with the permanent consultation process adopted by Statistics Canada with regards to CIP Canada.

How to provide feedback during the consultation?

Proposals for CIP Canada revisions must contain the contact information of those submitting the change request:

  1. Name
  2. Organization (when an individual is proposing changes on behalf of an organization)
  3. Mailing address
  4. Email address
  5. Phone number

Should additional information or clarification to the proposal be required, participants might be contacted.

Proposals must be submitted by email to: statcan.cip-consultation-cpe-consultation.statcan@statcan.gc.ca.

Consultation guidelines

Individuals or organizations are encouraged to follow the guidelines below when developing their proposals.

Proposals should:

  • clearly identify the proposed addition, change or modification to CIP Canada; this can include creating new classes, or modifying existing classes;
  • outline the rationale and include supporting information for the proposed change, such as:
    • title/name of the proposed new postsecondary educational program
    • curriculum of the proposed new program (the courses or subjects that make up the program)
    • names and number of educational institutions offering the proposed new program;
  • when possible, describe the empirical significance (i.e., field of study analysis, educational forecasting, comparing education and salary outcomes amongst groups) of proposed changes;
  • be consistent with classification principles (e.g., mutual exclusivity, exhaustiveness, and homogeneity within categories);
  • be relevant, that is
    • describe the present analytical interest;
    • enhance the usefulness of data;
    • base the proposal on appropriate statistical research or subject matter expertise.

Please consider the questions below when preparing your input for the consultation on the current version of the CIP Canada:

  • Are there postsecondary educational programs for which you cannot find a satisfactory CIP Canada code?
  • Are there classification items that you find difficult to use because their descriptions are vague or unclear?
  • Are there different postsecondary educational programs you find difficult to distinguish from each other? Are there boundaries that could be clarified?
  • Are there postsecondary educational programs that you think should have their own CIP Canada category? Please indicate at which level and why, with the support documentation about the postsecondary educational program (see guidelines above for a proposal).
  • Are there postsecondary educational programs that you are able to locate in CIP Canada, but you would like to have them located in a different 2-digit series or 4-digit subseries? And why?
  • Does the language or terminology used in CIP Canada need updating to be consistent with current usage?

Note that submissions do not need to cover every topic; you can submit comments on your particular area(s) of concern only.

The following criteria will be used to review the proposals received:

  • consistency with classification principles such as mutual exclusivity, exhaustiveness, and homogeneity of postsecondary educational programs within categories;
  • have empirical significance as a field of study;
  • data be collectable and publishable;
  • be relevant, that is, it must be of analytical interest, result in data useful to users, and be based on appropriate statistical research and subject-matter expertise;
  • special attention will be given to specific postsecondary educational programs, including:
    • new or emerging programs
    • changes related to the scope of existing programs.

CIP Canada Classification Structure

CIP Canada has a three-level hierarchical classification structure, consisting of 2-digit 'series', 4-digit 'subseries', and 6-digit 'instructional program classes'. Changes may be proposed for any level.

The Classification of Instructional Programs (CIP) Canada 2021 Version 1.0 is the latest version of the classification for participants of this consultation to base their input on. Persons or organizations proposing a change should always make sure they refer to the latest available version of CIP Canada.

Costs associated with proposals

Statistics Canada will not reimburse respondents for expenses incurred in developing their proposal.

Treatment of proposals

A team of representatives from Statistics Canada will review all proposals received. Statistics Canada reserves the right to use independent consultants, or government employees, if deemed necessary, to assess proposals.

If deemed appropriate, Statistics Canada will contact the respondents to ask additional questions or ask for clarification on a particular aspect of their proposal.

Please note changes will only be implemented during planned revision cycles and that a proposal will not necessarily result in changes to CIP Canada.

Official languages

Proposals may be written in either of Canada's official languages – English or French.

Confidentiality

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

Thank You

We thank all participants for their continued interest and participation in the various CIP Canada engagement activities.

Enquiries

If you have any enquiries about this process, please send them to statcan.cip-consultation-cpe-consultation.statcan@statcan.gc.ca.

Invitation to participate in the revision of the National Occupational Classification (NOC)

Opened: April 2024

Introduction

Statistics Canada (StatCan) invites data producers and data users, experts in the field of employment, representatives of business associations, government bodies at the federal, provincial/territorial, and local levels, academics and researchers and all other interested parties to submit proposals for the revision to the National Occupational Classification (NOC).

Following the decision of the Statistics Canada's Social Standards Steering Committee (SSSC) on January 9, 2024, to institute a permanent consultation process for the NOC, proposals may be submitted and reviewed on an ongoing basis. Only a cut-off date for considering proposed changes to be included into a new version of the NOC will be instituted moving forward.

As was done with the NOC 2016, in exceptional circumstances, when a consensus is reached among the data producers and users at StatCan and our partners at Employment and Social Development Canada (ESDC), the classification might be revised before the regular revision cycle of 10-years or update cycle of 5-years, as the way of 'evergreening' the standard.

In the context of statistical classifications, evergreening refers to updating the classification and the related reference (index) file on a continuous basis with the objective of maintaining quality, timeliness, and relevance. Though, evergreening does not necessarily result in the release of a new version of the classification every year. A decision to release a new version before milestone revision/update cycles needs to be discussed and assessed by key classification stewards considering potential impacts on data and statistical programs.

Objectives

This consultation aims to gather feedback from users who have already implemented the classification, as well as other interested parties who might want to suggest updates or changes. The principal objective of the consultation is to receive input from classification users to determine if the classification remains relevant and reflective of the Canadian labour market. This ensures that quantitative and qualitative information on occupations continues to be reliable, timely and relevant for a wide range of audiences.

Background

The NOC was jointly developed by ESDC and StatCan and has been maintained in partnership since the first edition published in 1991/1992. Prior to 2011, ESDC NOC and StatCan NOC-S differed in their major group structures and, consequently, in their coding systems. However, the revised NOC 2011 eliminated the differences between the two former systems.

In 2016 the NOC was updated as part of an every 5-year cycle content update, which generally occurs in response to labour market changes or to improve clarity and has no impact on data. Since 2016, ESDC and StatCan have implemented an "evergreen" practice for the NOC, where updates occur on an as-needed basis between the standard update/revision milestones. These "evergreen" updates strive to be constrained to specific situations or cases. For instance, in the NOC 2016 Version 1.2 the classification was revised to account for the new job titles created after Canada adopted a new law legalizing cannabis for non-medical use, with impacts on the whole Canadian economy and society.

Nature and content of proposals

Respondents are invited to provide their comments, feedback, and suggestions on how to improve the NOC, including a rationale for proposed changes. No restrictions have been placed on the type of change.

Respondents may propose virtual (not affecting the meaning of a classification item) and real changes (affecting the meaning or scope of a classification item, whether accompanied by changes in naming and/or coding or not). Examples of real changes are: the creation of new classification items, the combination or decomposition of classification items, as well as the elimination of classification items. A classification item (sometimes referred to as a "class") represents a category at a certain level within a statistical classification structure. It defines the content and the borders of the category, and generally contains a code, title, definition/description, as well as exclusions where necessary. For the NOC 2021V1.0, classifications items are: Major group (2-digit), Sub-major group (3-digit), Minor group (4-digit) and Unit group (5-digit).

Individuals and organizations wishing to submit proposals for changes in the NOC may do so at any time, in accordance with the permanent consultation process adopted by Statistics Canada with regards to the NOC.

How to provide feedback during the consultation?

Proposals for the NOC revisions must contain the contact information of those submitting the change request:

  1. Name
  2. Organization (when an individual is proposing changes on behalf of an organization)
  3. Mailing address
  4. Email address
  5. Phone number

Should additional information or clarification to the proposal be required, participants might be contacted.

Proposals must be submitted by email to statcan.noc-consultation-cnp-consultation.statcan@statcan.gc.ca

Consultation guidelines

Individuals or organizations are encouraged to follow the guidelines below when developing their proposals.

Proposals should:

  • clearly identify the proposed addition, change or modification to the NOC;
  • outline the rationale and include supporting information for the proposed change, such as:
    • approximate population of workers across the country;
    • duties;
    • requirements for certification (if any);
    • educational background, tools and technology used, as well as experience required for entry into the occupation;
    • current job titles used in the labour market;
  • when possible, describe the empirical significance (i.e., labour market analysis, career intelligence, occupational forecasting, employment equity, job training and skills development) of proposed change;
  • be consistent with classification principles (e.g., mutual exclusivity, exhaustiveness, and homogeneity within categories);
  • be relevant, that is
    • describe the present analytical interest;
    • enhance the usefulness of data;
    • base the proposal on appropriate statistical research or subject matter expertise.

Please consider the questions below when preparing your input for the consultation on the current version of the NOC:

  • Are there occupations for which you cannot find a satisfactory NOC code?
  • Are there classification items that you find difficult to use because their descriptions are vague or unclear?
  • Are there different occupations you find difficult to distinguish from each other? Are there boundaries that could be clarified?
  • Are there occupations that you think should have their own NOC category? Please indicate at which level and why, with the support documentation about the occupation or occupational grouping (see guidelines above for a proposal).
  • Are there occupations that you are able to locate in the NOC, but you would like to have them located in a different broad occupational category or TEER? And Why?
  • Is the language or terminology used in the NOC in need of updating to be consistent with current usage?

Note that submissions do not need to cover every topic; you can submit comments on your particular area(s) of concern only.

The following criteria will be used to review the proposals received:

  • consistency with classification principles such as mutual exclusivity, exhaustiveness, and homogeneity of occupational groupings within categories;
  • have empirical significance as an occupation output (labor force), input to labour market information)
  • data be collectable and publishable;
  • be relevant, that is, it must be of analytical interest, result in data useful to users, and be based on appropriate statistical research and subject-matter expertise;
  • occupations which can be used to create labour market information;
  • special attention will be given to specific occupations, including:
    • new or emerging
    • changes related to duties and requirements.

NOC 2021 Classification Structure

The NOC 2021 V1.0 is a 5-digit, 5-hierarchical level classification structure, consisting of 1-digit broad groups, 2-digit major groups, 3-digit sub-major groups, 4-digit minor groups, 5-digit unit groups. Changes may be proposed for any level.

The National Occupational Classification (NOC) 2021 Version 1.0 is the latest version of the classification for the participants of this consultation to base their input on. Persons or organizations proposing a change should always make sure they refer to the latest available version of the NOC.

Costs associated with proposals

Statistics Canada will not reimburse respondents for expenses incurred in developing their proposal.

Treatment of proposals

A team of representatives from Statistics Canada and ESDC will review all proposals received. Canada reserves the right to use independent consultants, or government employees, if deemed necessary, to assess proposals.

If deemed appropriate, Statistics Canada will contact the respondents to ask additional questions or ask for clarification on a particular aspect of their proposal.

Please note changes will only be implemented during planned evergreening or milestone revision/update cycles and that a proposal will not necessarily result in changes to the NOC.

Official languages

Proposals may be written in either of Canada's official languages – English or French.

Confidentiality

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

Thank You

We thank all participants for their continued interest and participation in the various NOC engagement activities.

Enquiries

If you have any enquiries about this process, please send them to statcan.noc-consultation-cnp-consultation.statcan@statcan.gc.ca.