2020-21 Annual Tracking Study/ Qualitative Research
Final report
Prepared for: Immigration, Refugees and Citizenship Canada
Supplier Name: Ipsos
Contract Number: B8815-21-0030/001/CY
Contract Value: $250,000.00 (including HST)
Award Date: 2020-07-29
Delivery Date: 2021-03-31
Registration Number: POR 019-20
For more information on
this report, please contact IRCC at:
IRCC.COMMPOR-ROPCOMM.IRCC@cic.gc.ca
Ce rapport est aussi disponible en
français.
Copyright
This public opinion research report presents the results of focus groups and two survey waves conducted by Ipsos on behalf of Immigration, Refugees and Citizenship Canada. Fourteen online focus groups were conducted between October 1st and November 2nd, 2020. The first survey wave was conducted with 1,500 Canadians by telephone and 1,503 online between August 21st and September 21st, 2020. The second survey wave was conducted with 1,501 Canadians by telephone and 1,500 online between February 18th and March 10th, 2021.
Cette publication est aussi disponible en français sous le titre : Étude de suivi annuelle 2020-21/ Recherche qualitative
This publication may be reproduced for non-commercial purposes only. Prior written permission must be obtained from Immigration, Refugees and Citizenship Canada. For more information on this report, please contact Immigration, Refugees and Citizenship Canada at IRCC.COMMPOR-ROPCOMM.IRCC@cic.gc.ca or at:
Communications
Branch
Immigration, Refugees and Citizenship Canada
Jean Edmonds Tower South
365 Laurier Ave W
Ottawa ON K1A 1L1
Catalogue Number: Ci4-183/2021E-PDF
International Standard Book Number (ISBN): 978-0-660-39934-8
Related publications
(registration number: POR 019-20):
Catalogue Number: Ci4-183/2021F-PDF (Final Report, French)
ISBN: 978-0-660-39935-5
© Her Majesty the Queen in Right of Canada, as represented
by the Minister of Immigration, Refugees and Citizenship Canada, 2021
Political Neutrality Statement
I hereby certify as Senior Officer of Ipsos that the deliverables fully comply with the Government of Canada political neutrality requirements outlined in the Communications Policy of the Government of Canada and Procedures for Planning and Contracting Public Opinion Research. Specifically, the deliverables do not include information on electoral voting intentions, political party preferences, standings with the electorate, or ratings of the performance of a political party or its leaders.
Mike Colledge
President
Ipsos Public Affairs
Table of Contents
Political Neutrality Statement
Quantitative Methodology (Wave 1)
Quantitative Methodology (Wave 2)
Appendix 1 – Quantitative methodology (Wave 1)
Appendix 2 – Quantitative methodology (Wave 2)
Appendix 3 – Qualitative and quantitative instruments
Executive Summary
Ipsos Public Affairs is pleased to present this report to Immigration, Refugees and Citizenship Canada.
Background
Since 1994, when it was established as a new department bringing together immigration services and citizenship registration, Immigration, Refugee and Citizenship Canada (IRCC) has played several key roles: admitting immigrants, foreign students, visitors and temporary workers; resettling refugees; helping immigrants adapt to Canadian society and become Canadian citizens; and managing access to Canada.
IRCC conducts an ongoing research program to help the Department develop a better understanding of Canadian attitudes toward the issues surrounding citizenship and immigration. By gauging and analyzing the opinions of newcomers, immigrants and the broader public, the Department gains insights into important policy areas related to the mandate of the Department and related services.
Research Objectives
This year’s study explored views of members of the Canadian general population, including newcomers and Indigenous Canadians, in the context of COVID-19. More specifically, the research objectives of this study included the following:
• Measure perceptions of the resumption of immigration to Canada once borders reopen;
• Measure perceptions of the number of immigrants coming to Canada;
• Measure perceptions of the impact of immigration on Canada;
• Measure perceptions of Canada’s immigration system and priorities;
• Measure perceptions of the settlement and integration of immigrants;
• Compare differences between online and telephone results and establish baseline online results where appropriate.
• Qualitative research to explore underlying sentiments, and to test statements pertaining to the reopening of Canada’s borders, and future immigration levels.
Attitudes of Canadians on issues such as immigration, settlement, integration, and citizenship as well as IRCC services are of key importance to IRCC’s policies and programs. By gauging and exploring attitudes about key elements of the department’s mandate, this research supports IRCC in ensuring high quality policy options, program design; encouraging and effectively managing citizen-focused services; managing organizational and strategic risks proactively; and gathering and using relevant information on program results.
The research project included two phases: a series of qualitative online focus groups and two waves of quantitative surveys conducted online and by telephone. The value of this contract, including HST, is $250,000.00.
Qualitative Methodology
Ipsos conducted 14 online focus groups in total with the following research audiences:
· Members of the Canadian general public 18 years of age or older (including those living in more rural areas of the country)
· Newcomers (immigrants who have lived in Canada for less than ten years)
· Indigenous Canadians (mix of regions)
Ipsos made use of special screening questions to ensure an appropriate mix of focus group participants based on income, age, education level, years in Canada and other relevant socio-demographic variables. Fieldwork took place between October 1st and November 2nd, 2020. Two focus groups were conducted each day, as per the following schedule:
1. October 1st, 2020
o Group 1: Greater Toronto Area
§ Research audience: General public
§ Language: English
o Group 2: Winnipeg, Saskatoon, Regina
§ Research audience: General public
§ Language: English
2. October 5th, 2020
o Group 1: Calgary, Edmonton
§ Research audience: General public
§ Language: English
o Group 2: Metro Vancouver
§ Research audience: General public
§ Language: English
3. October 6th, 2020
o Group 1: Greater Montreal
§ Research audience: General public
§ Language: French
o Group 2: Smaller centres in Quebec
§ Research audience: General public
§ Language: French
4. October 7th, 2020
o Group 1: Atlantic (mix of larger and smaller centres)
§ Research audience: General public
§ Language: English
o Group 2: Smaller centres in Western Canada, including Rural and Northern Immigration Pilot (RNIP) Communities
§ Research audience: General public
§ Language: English
5. October 13th, 2020
o Group 1: Smaller centres in Ontario, including Ontario RNIP Communities
§ Research audience: General public
§ Language: English
o Group 2: Indigenous Canadians, National (mix of regions)
§ Research audience: Indigenous Canadians
§ Language: English
6. October 14th, 2020
o Group 1: Greater Toronto Area
§ Research audience: Newcomers (immigrants who have lived in Canada for less than ten years)
§ Language: English
o Group 2: Metro Vancouver
§ Research audience: Newcomers (immigrants who have lived in Canada for less than ten years)
§ Language: English
7. November 2nd, 2020
o Group 1: Metro Vancouver
§ Research audience: General public
§ Language: English
o Group 2: Greater Toronto Area
§ Research audience: General public
§ Language: English
Online focus groups were approximately 2 hours in duration. A total of 103 participants took part in the discussions, out of 112 recruited to participate. Participants from the newcomer groups were provided a $125 incentive to encourage participation among these low incidence audiences. Other participants received an $85 incentive for their participation.
Note to reader: It should be noted that qualitative research findings are exploratory and directional in nature. Consequently, all qualitative findings cannot and should not be extrapolated to the Canadian population, rather, they should be valued for uncovering the depth and range of opinions in the population on the issues.
Quantitative Methodology (Wave 1)
Ipsos conducted a 14-minute telephone survey with a nationwide sample of n=1,500 Canadian adults between August 21st and September 21st, 2020, and a 10-minute online survey with 1,503 respondents between August 28th and September 21st, 2020.
The telephone survey sample was a probability sample generated through random digit dialing obtaining an overall margin of error of +/-2.5 percentage points (calculated at a 95% confidence interval). The online survey sample was non-probability, meaning that a margin of error cannot be calculated. Respondents were offered the survey in the official language of their choice.
A full quantitative methodology report, including all information about the execution of the fieldwork that is needed to replicate the research initiative, can be found in Appendix 1. The quantitative survey research instruments and a set of tabulated results from the quantitative surveys are provided in English and French under separate cover.
Quantitative Methodology (Wave 2)
Ipsos conducted a 15-minute telephone survey with a nationwide sample of n=1,501 Canadian adults between February 18th and March 10th, 2021, and a 14-minute online survey with 1,500 respondents between February 26th and March 10th, 2021.
The telephone survey sample was a probability sample generated through random digit dialing obtaining an overall margin of error of +/-2.5 percentage points (calculated at a 95% confidence interval). The online survey sample was non-probability, meaning that a margin of error cannot be calculated. Respondents were offered the survey in the official language of their choice.
A full quantitative methodology report, including all information about the execution of the fieldwork that is needed to replicate the research initiative, can be found in Appendix 2. The quantitative survey research instruments and a set of tabulated results from the quantitative surveys are provided in English and French under separate cover.
Key Qualitative Findings
The role of immigration in the COVID-19 economic recovery
· Across all groups, many viewed immigration as more likely to be helpful than harmful to the COVID-19 recovery. This view was underpinned mostly by the perceived net economic contribution of newcomers in general and in reference to the pandemic response (i.e., newcomers’ contribution to essential services and long term care homes).
· Having said that, there were a number of participants who were more likely to point to the potential harmful impact of immigration during the economic recovery from COVID-19. This included a small group of participants who declared themselves as usually pro-immigration but were unsure or hesitant in the context of COVID-19. Much of this sentiment was primarily driven by economic concerns as opposed to public health concerns.
· Concerns related to the potential economic harm of immigration during the COVID-19 recovery stemmed from the current state of Canada’s economy and labour market, with some emphasizing that we need to “look after people already in Canada first.”
· Overall, the net effect of the tested statements on the role of immigration in the COVID-19 recovery shown in the group discussions was to largely reinforce participants pre-existing views towards immigration. The statements’ core points rung true for many – especially in reference to immigrants’ contribution to the healthcare system – but this did not always translate into emphatic support for resuming immigration.
· The same participants who were sceptical towards immigration responded negatively to what they perceived as overly positive language and/or tone of messaging on the benefits of immigration.
Canada’s immigration levels
· There was general support for the proposed 2021 levels (presented in the first twelve groups as 351,000 immigrants, based on the then-current 2020-2022 Immigration Levels Plan, and as 401,000 in the final two groups, which took place after the revised 2021-2023 Immigration Levels Plan was tabled in Parliament). The large proportion allocated to skilled immigrants and the inclusion of immigration levels phrased as 0.92% of Canada’s population were key in underpinning support.
· Still, there was a view among some participants that the proposed levels are too high due to the current economic climate. This led to calls from some to “take a pause” on immigration and prioritize Canadian workers until Canada’s economy recovers from the pandemic.
· Reactions to admitting 500,000 immigrants (or 1.3% of the Canadian population) were similar to those expressed regarding the 2021 immigration levels, whilst the option of doubling levels was typically met with some hesitation and more red flags being raised. The preference was for increases to be slow and gradual, which for some would prevent drastic changes to the fabric of society.
· All in all, it was evident that participants somewhat struggled with what the “right” level of immigration should be and were much more comfortable in voicing a preference on which classes of immigrants should be prioritized and the need to divert newcomers to rural areas.
· When shown the breakdown of different immigration classes, there was general agreement with the distribution. Some were pleasantly surprised that the economic class makes up the highest proportion, and by the smaller proportion of spaces being awarded to other categories, including refugees.
· There was strong consensus that skilled workers should be prioritised. Participants’ definition of ‘skilled’ encompassed highly educated professionals such as doctors as well as other skills where there are shortages.
· References to the family and refugee classes tended to result in more divisive conversations than the economic class.
Messaging on increasing levels
· Overall, messages on Canada’s low birth rate and its ageing population were most effective in garnering a broad base of support and in communicating a sense of urgency around the need for immigration and to some extent higher levels of immigration.
· The statistic that there are ‘4 Canadian workers for every retired Canadian, but by 2035, there will be only 2 workers for every retiree’ was especially “powerful” in making the case for increasing levels.
· Individually and collectively though the messages shown in the discussions had a limited effect on the few participants who were decidedly negative towards immigration; they did not challenge the issues presented, rather they pushed back at the seeming portrayal of immigration as the main or only solution and repeated calls for looking after Canadians first.
Impact of immigration
· Measures for successfully welcoming newcomers tended to skew more towards alleviating the added pressures on communities receiving newcomers than on settlement supports for newcomers. More affordable housing and transport infrastructure were top-of-mind, followed by less frequent mentions of funding for more teachers and reducing wait times in the healthcare system.
· Finally, this qualitative study provided the opportunity to explore the factors that lead some Canadians to say that immigration is causing Canada to change in ways they do not like. There was a general consensus that this sentiment is by and large underpinned by the cultural impact of immigration, though the majority of focus group participants reported that they did not feel this way.
· A few participants were willing to explain why someone would hold that view: feeling like they are “the only English guy at work” and a perception that not all newcomers make an effort to learn/use English or French, lamenting the “loss of traditional Canadian ways of living” and traditions whilst newcomers stay in their “ethnic enclaves,” and the perception that Canadians are asked to make a strong effort to “accommodate their cultures”, as opposed to the other way around.
· A notable number of participants meanwhile were quick to label this sentiment as “racism” which they attributed to “ignorance”, misunderstanding and discomfort with the changing make-up of Canada’s population and customs.
Should you have any questions or comments, please contact:
Marc Beaudoin
Vice President Qualitative, Ipsos UU
1 Nicholas, Ottawa Ontario
Telephone: (613) 688-8973
Email: marc.beaudoin@ipsos.com
Detailed Qualitative Findings
a. The role of immigration in the COVID-19 economic recovery
Attitudes towards the role of immigration in the COVID-19 recovery tended to fall based on participants’ pre-existing (i.e., before the pandemic) sentiment towards the issue. Across all the groups, many viewed immigration as more likely to be helpful than harmful to the COVID-19 recovery. This view was underpinned mostly by the perceived net economic contribution of newcomers which was discussed on three levels:
· The material impact to the economy based on the belief that newcomers “bring in money” and create demand for local goods and services;
· The “hardworking” work ethic of newcomers meaning that they fill jobs that “Canadians don’t want to do” along with an “entrepreneurial spirit” that results in new businesses; and
· Addressing workforce shortages in essential sectors including in the healthcare sector.
Having said that, there were a number of participants who were more likely to point to the potential harmful impact of immigration during the economic recovery from COVID-19. It was evident that a subset of these participants skewed more negative on the effects of immigration in general. What was notable, however, was a small group of participants who declared themselves as usually pro-immigration but were unsure or hesitant in the context of COVID-19 (“now is not the right time”). Much of this sentiment was primarily driven by economic concerns as opposed to public health concerns. When the latter were raised by a handful of participants, there was a preference for keeping the border closed and selecting applicants based on countries with lower COVID-19 case counts. There was general trust that appropriate precautions are being taken to mitigate community transmission from newcomers arriving.
Concerns related to the potential economic harm of immigration during the COVID-19 recovery stemmed from the current state of Canada’s economy and the financial precarity faced by Canadians who have lost their jobs due to the pandemic. This led some to emphasize that we need to “look after people already in Canada first”. Concerns were also raised about the ability of newcomers to find employment and successfully integrate in light of the current COVID-19 environment. Concerns about the benefits of proceeding with immigration at this time continued to be registered when statements were shown on the benefits of immigration during the COVID-19 recovery (more details below).
Finally of note, participants who were sceptical towards immigration in general responded negatively to what they perceived as overly positive language and/or tone of messaging on the benefits of immigration, as it was perceived to implicitly negate the contributions of Canadians. This remained true even when these participants were asked to consider the role of immigration after the COVID-19 risks are over. These participants generally felt that the economic repercussions and challenging labour market conditions may linger after the public health crisis is contained.
Overall, the statements shown in the group discussions on the role of immigration in the COVID-19 recovery reinforced participants’ initial reactions outlined above.
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Immigration was a Canadian advantage before the pandemic, immigrants are helping Canadians through the pandemic right now and immigration will be critical to Canada’s economic recovery. |
The statement spoke to the widespread belief of Canada “being a country of immigrants” and thus there was little challenge to the notion of immigrants being of benefit to the country before and during the pandemic. Beyond the economic benefits of immigration, there were references to immigrants’ contribution to the country’s cultural diversity and “bringing in new ideas”. Still, this statement did little to sway those who expressed concerns on immigration’s potential strain on limited jobs in the immediate future and the need to “let Canada heal itself first”. The word ‘critical’ was flagged as somewhat of an overreach; it was pointed out that a combination of measures will be needed for Canada to recover and, for a subset of participants, immigration is unlikely to be the key one.
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When immigrants arrive in a community, they create new demand for local products and services, including housing, transportation and food. They also start businesses and create jobs—33% of business owners with paid staff are immigrants. |
The economic benefits expressed in this statement “went without saying” for participants who held the most positive views towards immigration; there was a clear sense that the current pandemic situation has not changed their stance on this in either direction.
This statement however raised more questions than answers for others. Mention of ‘housing’ and ‘transportation’ tended to spark discussion on the pressures immigration puts on infrastructure: participants in Metro Vancouver spoke of the “housing crisis” as did those in Montreal; those in major centres of Atlantic Canada referred to the “.1% vacancy rate”; and those in Greater Toronto Area also spoke of availability of housing along with congestion and overcrowding on the TTC.
Similarly, the added detail on job creation by immigrants led to questioning on whether this would continue in the ongoing COVID-19 economic climate as they’ve seen how businesses, including local “institutions”, around them have struggled. This was complemented by a belief that it takes time for immigrants to become established enough to set up a business, thus the benefit is likely to be reaped in the longer-term. In turn, questions were raised about how ‘an immigrant’ was defined in the context of the 33% statistic.
Whether all Canadians benefit from jobs created by immigrants was questioned in some groups by participants from smaller and more rural centres in Ontario and to a lesser degree those in rural Quebec. There was an impression among some that jobs created by immigrants tend to go to those from the same ethnocultural background.
All in all, among those who had reservations, the pairing of ‘create new demand’ with ‘start businesses and create jobs’ had limited success in making the case for resuming immigration to support the economic recovery.
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Figure 3: Statement 3 Immigration helps ensure Canada has the health care workers it needs to keep Canadians safe: 25% of all health care workers are immigrants, including 36% of family physicians. Almost half a million workers in the health care sector are over the age of 55, and as they retire, existing recruitment challenges for nurses, residential care staff and home health care staff will be worsened. |
Immigrants’ contribution to the healthcare system rung true for many, with a number of participants going on to share personal stories: positive experiences of having recently switched to a family doctor who immigrated to Canada; having a family doctor who is close to retirement age; working in the HR department of a hospital where there’s a “crisis” in filling positions. There was acknowledgment of shortages across the board from personal health workers to nurses and doctors, and the need extended well beyond COVID-19. This statement has strong personal resonance and it was emphasized throughout the discussions that doctors and nurses are skilled workers that should be prioritised moving forward.
Despite these positive reactions, it was pointed out that Canada does not recognize the qualifications of foreign trained healthcare workers (foreign credential recognition - FCR) meaning that it takes several years for them to retrain and for the system to benefit. Furthermore, there was a view, among participants most sceptical regarding immigration and in line of the theme of looking after ‘Canadians first’, that this statement speaks to international students displacing Canadian-born students in post-secondary institutions in health fields and the general unaffordability of this type of training for Canadian-born students. Others did not feel that the statement clarified the need for immigration to resume, even though they recognized immigrant health care workers’ contribution during the pandemic.
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Immigrants contribute to Canada’s tax base, making it possible for Canada to afford social programs such as health care and elder care, as well as infrastructure projects and other goals that matter to Canadians such as environmental protections. |
While the general sentiment was that immigrants do indeed contribute to Canada’s tax base, there was some nuance in viewpoints. On the one hand, this was seen as a natural and logical extension of the perception that immigrants are “hardworking”. This link however was not always obvious to some participants, with one participant, for example, admitting that she “had never thought of immigration in this way”; as a result of this statement, some participants came to recognize that immigrants don’t merely use services, but also contribute to them.
A few meanwhile felt that immigration is “probably revenue neutral” once one factored in immigrants’ use of services and infrastructure. This position did not translate into an anti-immigration sentiment, rather it came across as a measured outlook on the issue by accounting for the counterargument.
Some tended to question how much immigrants contribute to the tax base and this sentiment was not always exclusive to those who held a more negative view on immigration. Reasoning for this stemmed from a range of perceptions:
· immigrants tend to take lower paying jobs, especially when they first arrive, or are unable to find employment in the COVID-19 context;
· they bring spouses and family members who may not work but use services and infrastructure nonetheless; and
· refugees tend to require government funding to help them settle in Canada.
In one of the Metro Vancouver groups, there was a further view that wealthy immigrants opt to register as unemployed to claim benefits in addition to using services.
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Figure 5: Statement 5 Immigration has historically helped Canada’s economy become one of the most successful in the world. |
While not asked in all groups, there was positive yet somewhat muted reception to this statement. The word “historically” was flagged as problematic in the group with Indigenous Canadians given the historical context of Canada’s treatment of their community.
b. Canada’s immigration levels
Maintaining 2021 levels
There was general support for the proposed 2021 levels (presented in the first twelve groups as 351,000 immigrants, based on the then-current 2020-2022 Immigration Levels Plan, and as 401,000 in the final two groups, which took place after the revised 2021-2023 Immigration Levels Plan was tabled in Parliament). The large proportion allocated to economic class immigrants (presented to participants as “either immigrants selected because of their skills, education or experience or family members of these people”) and the inclusion of immigration levels phrased as 0.92% of Canada’s population (this information was presented along with the 2021 levels) were key in underpinning support. Participants expected skilled immigrants to help Canada economically, 0.92% seemed “reasonable” and status quo had proven manageable if nothing else. Still, it is worth noting that some of the support came with caveats: the proposed 2021 levels would be appropriate when Canada has recovered from the pandemic as there would be more jobs available; and encouraging immigration to rural areas of Canada. Support for spreading immigration to rural communities stemmed mostly from belief that Canada has a lot of space to accommodate more people; a desire to reduce the strain of immigration on the infrastructure of larger centres (such as housing, public transit, and social services); and the need to address labour shortages and population decline in rural communities.
Despite broad support for the proposed 2021 levels, a few participants felt that the government is admitting “too many” immigrants stemming from the current economic climate. With the current unemployment rate, these participants were concerned about Canadians competing with immigrants for jobs. Moreover, they were of the view that government cannot afford immigration services with the growing deficit to fund COVID-19 efforts. This led to calls of the need to “take a pause” on immigration and prioritize Canadian workers until Canada’s economy recovers from the pandemic. Concerns regarding housing, infrastructure and availability of social services (healthcare and education) were reiterated at this point in the discussions.
Very few participants thought Canada is admitting ‘too few’ immigrants. Where this was the case, participants had a strong view of Canada as an “open” and “welcoming country” and they had a higher level of pre-awareness of Canada’s declining population.
More broadly, it was evident that participants somewhat struggled with what the “right” level of immigration should be and were much more comfortable in voicing a preference on which classes of immigrants should be prioritized and the need to divert newcomers to rural areas.
In the two groups conducted after the 2021-2023 Immigration Levels Plan was tabled in Parliament, there was little spontaneous awareness of the announcement of the immigration levels set for the next three years. The discussions in these groups were very much in line with the themes outlined above.
Scenarios for higher levels
Reactions to admitting 500,000 immigrants (or 1.3% of the Canadian population) fell out similarly to those expressed regarding 2021 immigration levels. There were additional caveats raised by those who tentatively supported increased levels including a desire for increases to happen at a slow, measured rate, and questions around the necessity of increasing levels. Those who tended to be opposed to further increases pointed out that maintaining a target that is a percentage of Canada’s population would result in increases in absolute numbers anyway.
Participants typically met the option of doubling levels with some hesitation as this notion raised more red flags. It simply felt somewhat alarming and the preference was for increases to be slow and gradual, which for some would prevent drastic changes to the fabric of society.
Again, there were repeated calls made in all groups that concerted efforts should be made to encourage newcomers to settle in less densely populated areas rather than Canada’s larger metropolitan areas.
When shown the breakdown of different immigration classes, some were pleasantly surprised at the fact that economic-class immigrants made up the highest proportion, and by the smaller proportion of spaces being awarded to other categories, including refugees. This was noted by a few as a stark contrast to the picture painted by the media, who indicated that they had been under the impression that a majority of immigrants to Canada were refugees.
There was strong consensus that skilled workers should be prioritized, and though some took comfort at the proportion already allocated to the economic class, others wanted to see this proportion increased further, particularly given that this class includes dependents – indeed, the inclusion of family members alongside skilled workers undermined confidence in the percentage of the economic class provided to participants. Participants’ definition of ‘skilled’ encompassed highly educated professionals such as doctors as well as any other skills where there are shortages. There was trust in government to identify relevant fields. With respect to desirability of skilled workers, participants did not tend to distinguish between “high” skilled and “low” skilled workers, though a few raised concerns regarding the overrepresentation of immigrants (including skilled immigrants struggling with credential recognition) in lower-skilled fields such as retail, as something that could potentially displace Canadians from these fields.
Discussions related to the family class tended to result in more negative comments than the economic class. There was an assumption that family members would include spouses or elderly family members who are less likely to speak English or French, are less likely to contribute economically, but are likely to use social programs and infrastructure nonetheless. These negative comments were sometimes countered by awareness of the fiduciary responsibility of their sponsor, the emotional support family members provide and the economic contribution of family members.
The percentage allocated to refugees was divisive, with some saying that 15% of all new immigrants is too few, and others that it is too many. Those who felt that Canada cannot afford to admit and support refugees—particularly right now, as a result of COVID-19—tended to be more vocal, but a few participants argued that Canadians should “do our part” to help those living in less fortunate circumstances, and that this was part of what it means to be Canadian.
c. Messaging on increasing levels
Participants were asked to consider the role of immigration in a post-COVID-19 world and were presented with a series of messages that underscored the importance of increasing levels of immigration. Overall, messages on Canada’s low birth rate and its ageing population were most effective in garnering a broad base of support and in communicating a sense of urgency around the need for immigration and to some extent higher levels of immigration.
Individually and collectively, though, these messages had a limited effect on the few participants who were decidedly negative towards immigration; they did not challenge the issues presented, rather they pushed back at the seeming portrayal of immigration as the main or only solution and repeated calls for looking after Canadians first.
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Figure 6: Message 1 Canada will need to increase our annual immigration levels or else our economy will shrink in the future as more Canadians retire than enter the workforce. Because of lower birth rates in recent decades, Canada’s population is not replacing itself. Our population will shrink over time, unless we increase the number of immigrants allowed to come to Canada. |
Participants expressed little surprise or doubt around the core argument on Canada’s ageing workforce and declining birth rates in this message – it was almost taken as a given. Reactions took on a mostly ‘matter-of-fact’ and rationalist tone - i.e., “immigration is the next logical step” as “we’re not shaking people out of our sleeve”. A small number of participants went on to connect the dots on the implications of a shrinking workforce/population on CPP and future generations’ prospects on retirement, the affordability of our healthcare system and sustaining rural populations.
Participants were first shown the first paragraph, followed by the first and second paragraphs together. Once shown the message in its entirety, the underlying message became much more convincing to most participants. While some reported being aware of lower birth rates, the added detail provided necessary context to improve the credibility of the statement. There were further calls to provide “the numbers” to back it up.
This message was challenged by a handful who took issue with the assumption that the economy would shrink – this partly stemmed from an attitude of it is simply not possible to know and partly pointing to an increased reliance on automation and how this change could impact traditional jobs. These views tended to refocus the discussion on the financial burden of raising a family in Canada. Rather than immigration, these participants called on government to provide more supports to families to enable Canadians to have more children – this view was expressed on a number of occasions among participants from Quebec and in western Canada. Younger participants in the smaller communities in western Canada pushed back on this narrative by pointing out their decision to not have any or only have 1 child was a matter of lifestyle “choice”.
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Figure 7: Message 2 Canada will need to increase our annual immigration levels or else we will find ourselves with a decline in the tax revenues we need to pay for health care, education and other programs Canadians depend on. There are currently 4 Canadian workers for every retired Canadian, but by 2035, there will be only 2 workers for every retiree. Without immigrants to help support the needs of an aging population, younger Canadians will have to provide enough income tax to support elderly Canadians, they end up paying more per person to provide the same benefits. |
Highlighting the implications of an ageing workforce on the tax base was more effective than messaging on a shrinking economy in making the case for increasing immigration levels. The statistics quoted were deemed to be “powerful” and “painted a clear picture” that “wow, we could be in trouble”, resulting in a heightened level of support for immigration. Younger participants, those who felt that they were being “taxed through the roof” already and those in retirement were among the most likely to vocally reflect on how they could be personally worse off without increasing levels of immigration. The message thus succeeded in encouraging participants to consider immigration in a somewhat new manner that was tangible to their lives.
The few who reacted negatively to this statement tended to feel that it discounts the fact that Canada is a “strong” and “well-developed” country with “millions of Canadians” that pay into the tax base. There was a clear sense that this too ties into the narrative of overlooking Canadians and presenting immigration as the only solution. This in turn led some to wonder whether the focus should be on reducing government spending and what other countries are doing. Notably, unlike message 1 that emphasised a shrinking economy, there was less discussion on the need to increase birth rates of Canadians as it was acknowledged that it takes time to “turn baby Canadians into taxpayers”.
Where there was a very negative view of the family class category in one group with Metro Vancouver participants, this statement resulted in a heightened concern of older immigrants being sponsored to Canada and their net effect on Canada’s social system.
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Figure 8: Message 3 As other countries turn away from immigration, Canada should take advantage of this opportunity to increase our intake of diverse and talented workers from around the world who are looking for a destination that is welcoming to and supportive of immigrants. |
On the one hand, the message was well-received as it dovetails with the strong calls made in all groups for Canada to prioritize high skilled workers. Several participants saw this as an opportunity for Canada to pick the best of the best of skilled workers in the face of anti-immigration sentiment in other countries (there were a couple of references made to the USA). Reactions were similarly positive when told that a diverse workforce could attract high-tech firms to set up offices in Canada.
That said, the message did not provide a compelling case as to why immigration levels should increase and few latched on to the notion that this presents a unique opportunity or competitive advantage for Canada. The message resonated mostly as it reflected preferences in who should be admitted irrespective of whether levels are maintained or increased.
Further, some failed to see the link between why Canada’s policy should change in light of what other counties are doing and preferred for policy to be driven by internal needs. Others meanwhile wondered why other countries are turning away from immigration. Others still felt that the priority should be to retrain and educate Canadians to create a diverse workforce.
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Canada should increase our annual immigration levels in order to increase Canada’s population, which would grow the economy and increase our self-reliance in an uncertain world. |
This message was least appealing among participants in all groups. The self-reliance argument resonated to some extent for a few who made a link to the lack of personal protective equipment earlier in the year and the USA “being a wildcard” these days.
Meanwhile, a larger population being a positive in-and-of-itself was not a compelling argument for most. Participants generally struggled to come up with tangible benefits of Canada having a larger population. Beyond growing the economy, the best they could point to was that Canada has the space to accommodate more people and perhaps some economies of scale. Asked whether a larger population would result in Canada having more influence in the world, this was countered with “Do we not have a lot of influence right now?” Similarly, response was somewhat muted when presented with the argument of a more manageable national debt with a larger population.
All in all, the message was perceived as somewhat vague and counterintuitive – i.e., having to rely on others to become more self-reliant. The message did little to sway those who felt strongly that immigration policy should be driven by bringing newcomers with the necessary skills, as opposed to focusing on the absolute numbers. It further exacerbated concerns of lack of housing and other infrastructure to support more newcomers.
|
Figure 10: Message 5 “The secret to Greater Moncton’s recent economic success is that the jobs’ pie is large enough for both native-born Canadians and newcomers. We need to increase our population and labour force through every way possible to seize the economic opportunity now before us.” Moncton Chamber of Commerce, 2018 “We desperately need immigration. We are an aging society that in 10 or 15 years will be totally dependent on immigrants that we are getting now.” Deputy Chief Economist at CIBC, 2020 |
According to participants, the business community and local business organizations are credible messengers when it comes to skills shortages that immigration could address. Participants in Quebec for example spoke of how they had seen first-hand on a day-to-day basis how immigration directly impacts the economy at the local and national level. It was further noted in the group with Albertans that business organizations could be a force for changing the generally negative narrative on immigration.
Yet, there were clear limits to how far this type of messaging can reach. The assertion that we ‘will be totally dependent on immigrants’ appeared to be less effective than providing hard-hitting statistics as per other messages. There was also some general mistrust towards big business as they were viewed as self-interested actors who could be motivated by factors other than the public good (e.g., driving down wages). To counter this, quotes from “grassroot” sources such as the Moncton Chamber of Commerce were seen as more effective, albeit at the expense of the applicability of the message to larger geographies.
One participant in the Indigenous Canadians group pointed out that the use of ‘native’ may not be the best choice of words and could be off-putting to some in their community.
d. Impact of immigration
Measures for successfully welcoming newcomers tended to skew more towards alleviating the added pressures on communities receiving newcomers than on settlement supports for newcomers. More affordable housing and transport infrastructure were top-of-mind, followed by less frequent mentions of funding for more teachers and reducing wait times in the healthcare system. Calls to encourage newcomers to “spread out” to less populous provinces and towns and putting in place appropriate infrastructure to accommodate more people were repeated.
On settlement supports mentioned by some, emphasis tended to fall on helping newcomers adapt to daily life in Canada such as how to access services, driving, official languages and dealing with Canadian winters. Complementing this, a handful of participants pointed to the importance of having welcoming communities and mentorship support provided to newcomers, such as was done with Syrian refugee sponsorship.
Recognizing immigrants’ education or certificates, or at least expediting the process of obtaining equivalent Canadian qualifications, was reiterated as necessary to harness their skills. Moreover, “transparency” around the type of immigrants being admitted to Canada and highlighting their value, especially to smaller centres, were pointed out in a couple of groups as important in winning the support of the public on the issue.
Finally, this qualitative study provided the opportunity to explore the factors that lead some Canadians to say that immigration is causing Canada to change in ways they do not like.
Although there were some references to pressures newcomers put on social programs and infrastructures and the creation of programs for newcomers specifically, there was a general consensus that this sentiment is by and large underpinned by the cultural impact of immigration, though the majority of focus group participants reported that they did not feel this way. This sentiment of ‘Canada changing’ was clearly shared by a small number of participants in the discussions, or encountered by others in their circles, and stemmed from:
· lamenting the “loss of traditional Canadian ways of living” and traditions (“no more Christmas concerts in schools”) whilst newcomers stay in their “ethnic enclaves,” and the perception that Canadians are asked to make a strong effort to “accommodate their cultures”, as opposed to the other way around.
Muslim communities were sometimes singled out in these comments but most of the comments were in reference to immigrants in general. Also of note, and consistent with past IRCC research, is that some immigrants themselves shared these negative impressions on other immigrants’ impact on the cultural fabric of Canada.
A notable number of participants meanwhile were quick to label this sentiment as “racism” which they attributed to “ignorance”, misunderstanding and discomfort with the changing make-up of Canada’s population and customs.
e. Nuances by subgroups
There was remarkable similarity in the findings across the subgroups targeted. Some nuances found include:
· GTA/Metro Vancouver – They were most likely to express concerns with immigrants settling in large cities and the economic and social burden this can have on urban centres in terms of availability of services, employment opportunities and housing. There was a suggestion that the government can offer incentives in order to encourage newcomers to seek out alternative locations with lower population density. There were also mentions (mostly in Vancouver) of mansion owners living in upscale neighbourhoods declaring less income in order to receive welfare benefits.
· Rural/Atlantic – Participants from rural areas and the Atlantic Provinces were more open to immigration and to future increases. They recognized the importance of immigrants in terms of their contributions in taxes, economic growth and population growth in their areas. Those from the east coast had the impression that young residents in the Atlantic Provinces tend to find work in large urban centres in other provinces and these participants therefore viewed immigration as a solution to this problem.
· Indigenous Canadians – Participants were mostly supportive of current levels and increases. Many of them had positive experiences with immigrants and viewed them as valuable contributors to local communities. Caution on the term ‘native-born Canadians’ was urged.
· Newcomers – While other groups tended to skew negative towards family class, newcomer groups were more likely to point out mental health benefits of the family reunification class and their economic benefits to society in general. However, newcomers were more likely to express concerns about Canada’s capacity to welcome refugees – specifically the necessary financial help and programs to assist refugees with their integration into Canadian society.
· French-speakers – Some participants in Quebec groups referred to the notion of ‘Quebecois de souche’ or natural born Quebecers. Comments and concerns expressed tended to focus on what some see as the gradual loss of ‘identity’ and the potential impact a reliance on immigration could have on their ‘culture’. To further underscore this perspective some participants specifically pointed to the ongoing debate related to religious tolerance and the need for secularism in public spaces which has occupied the public discourse in the province for some time now.
Appendix 1 – Quantitative methodology (Wave 1)
Telephone survey
Ipsos conducted a 14-minute telephone survey among a nationwide sample of n=1,500 Canadian adults between August 21st and September 21st, 2020. The sample is a probability sample generated through random digit dialing. For respondents contacted on a landline, respondents within households were selected at random, by using the “birthday method” of identifying and interviewing the member of the household (aged 18+) who had their birthday last.
Respondents contacted on a cellular phone were also random digit dialed, and needed to be 18+ to participate. Wireless samples were selected on a provincial level (as it is not practical to accurately select by market given the mobile nature of the technology) from a database containing all possible numbers in 1000-blocks of area codes and exchanges dedicated to wireless numbers.
Within the total sample of 1,500 Canadians for this survey, 450 respondents were contacted on their landlines, while the other 1,050 respondents were contacted on their cellphones. The margin of error for a telephone survey of 1,500 respondents is ±2.5%, using a confidence interval of 95% (19 times out of 20). The final questionnaire used was provided by IRCC to ensure adequate tracking of previous research results conducted by the department.
Telephone sample weighting
The tables below indicate the unweighted and weighted distributions of the telephone sample. The sample was stratified by region, with soft quotas also set for gender and age to ensure appropriate representation across categories. Weighting was applied to the sample to ensure that the final data reflects the adult population of Canada by region, age and gender according to the 2016 Census.
Please note, the totals below may not add up to 1,500 due to some respondents’ refusal to provide socioeconomic information.
Weighted and unweighted telephone sample: Region (Variable included in the weighting scheme)
|
|
Unweighted sample size |
Weighted sample size |
|
British Columbia/Territories |
189 |
206 |
|
Alberta |
154 |
168 |
|
Saskatchewan |
99 |
45 |
|
Manitoba |
100 |
52 |
|
ON |
480 |
574 |
|
QC |
326 |
353 |
|
Atlantic Canada |
152 |
103 |
Weighted and unweighted telephone sample: Gender (Variable included in the weighting scheme)
|
|
Unweighted sample size |
Weighted sample size |
|
Male |
722 |
722 |
|
Female |
760 |
765 |
|
Another gender |
9 |
5 |
Weighted and unweighted telephone sample: Age (Variable included in the weighting scheme)
|
|
Unweighted sample size |
Weighted sample size |
|
18-24 |
122 |
164 |
|
25-34 |
209 |
246 |
|
35-44 |
265 |
242 |
|
45-54 |
264 |
269 |
|
55-64 |
294 |
262 |
|
65+ |
346 |
317 |
Weighted and unweighted telephone sample: Education
|
|
Unweighted sample size |
Weighted sample size |
|
High school or less |
239 |
234 |
|
Some post-secondary |
123 |
117 |
|
Trade school or college |
395 |
393 |
|
University |
738 |
751 |
Weighted and unweighted telephone sample: Income
|
|
Unweighted sample size |
Weighted sample size |
|
Under $40K |
261 |
265 |
|
$40K to under $60K |
194 |
194 |
|
$60K to under $100K |
383 |
374 |
|
$100K or more |
525 |
543 |
Weighted and unweighted telephone sample: Country of birth
|
|
Unweighted sample size |
Weighted sample size |
|
Born in Canada |
1158 |
1133 |
|
Born outside of Canada |
341 |
366 |
Statistics presented in the table above show minimal differences between the final unweighted and weighted samples. However, the youngest age group (18 to 24 years old) is underrepresented, resulting in a higher unweighted to weighted ratio.
Call dispositions
The following table provides the call dispositions and response rate calculation, as per the former MRIA’s empirical method of calculating response rates for telephone surveys.
|
Landline |
Cellphone |
Total |
|
|
16824 |
45375 |
62199 |
|
|
Invalid (NIS, fax/modem, business/non-res.) |
7866 |
28590 |
36456 |
|
Total unresolved units (Busy, no answer, answering machine) |
2887 |
8330 |
11217 |
|
Total in-scope - non-responding units |
2603 |
6133 |
8736 |
|
Language problem |
53 |
139 |
192 |
|
Illness, incapable, deaf |
20 |
16 |
36 |
|
Household refusal |
2480 |
5901 |
8381 |
|
Qualified respondent break-off |
50 |
77 |
127 |
|
Total in-scope - responding units |
455 |
1420 |
1875 |
|
Over quota |
5 |
17 |
22 |
|
No one 18+ |
0 |
353 |
353 |
|
Occupation Disqualified |
0 |
0 |
0 |
|
Completed interviews |
450 |
1050 |
1500 |
The response rate, calculated as the number of in-scope – responding units divided by the sum of unresolved units, in-scope – non-responding units, and in-scope – responding units, was 7.65% for landline numbers, 8.94% for cellphone numbers, and 8.59% for all telephone numbers. The total response rate of 8.59% for a telephone survey of the Canadian general population with up to 8 call-backs per household is typical.
Non-response analysis
As with any probability sample, there exists within the current sample the possibility of non-response bias. In particular, this survey would not include members of the population who do not have access to a telephone (either landline or cell phone) or who are not capable of responding to a survey in either English or French. In addition, some groups within the population are systemically less likely to answer surveys.
The table below compares the unweighted sample to the 2016 Census results by region, age, gender, education, income and country of birth. The comparison between the two samples for the three variables used in the weighting scheme (using interlocking weights for region with age and region with gender) shows a slight underrepresentation of younger Canadians (18 to 24 years of age). However, this discrepancy is small enough that it can be corrected through weighting without affecting the quality of the final results. As the regional distribution was set through hard quotas, the weighting had virtually no impact on final numbers.
Telephone sample population comparison: Region (Variable included in the weighting scheme)
|
|
Unweighted percentage |
Census 2016 proportions (adults) |
|
British Columbia/Territories |
13% |
14% |
|
Alberta |
10% |
11% |
|
Saskatchewan |
7% |
3% |
|
Manitoba |
7% |
4% |
|
ON |
32% |
38% |
|
QC |
22% |
24% |
|
Atlantic Canada |
10% |
7% |
Telephone sample population comparison: Gender (Variable included in the weighting scheme)
|
|
Unweighted percentage |
Census 2016 proportions (adults) |
|
Male |
48% |
49% |
|
Female |
51% |
51% |
Telephone sample population comparison: Age (Variable included in the weighting scheme)
|
|
Unweighted percentage |
Census 2016 proportions (adults) |
|
18-24 |
8% |
11% |
|
25-34 |
14% |
16% |
|
35-44 |
18% |
16% |
|
45-54 |
18% |
18% |
|
55-64 |
20% |
18% |
|
65+ |
23% |
21% |
Telephone sample population comparison: Education
|
|
Unweighted percentage |
Census 2016 proportions (adults) |
|
High school or less |
24% |
43% |
|
Trade school or college |
26% |
35% |
|
University or higher |
49% |
22% |
Telephone sample population comparison: Income
|
|
Unweighted percentage |
Census 2016 proportions (adults) |
|
Under $40K |
17% |
26% |
|
$40K to under $60K |
13% |
16% |
|
$60K to under $100K |
26% |
25% |
|
$100K or more |
35% |
32% |
Telephone sample population comparison: Country of birth
|
|
Unweighted percentage |
Census 2016 proportions (adults) |
|
Born in Canada |
77% |
78% |
|
Born outside of Canada |
23% |
22% |
This comparison between the unweighted sample distribution and the actual population figures for variables not included in the weighting scheme shows that the final sample obtained was mostly representative of the general population for this survey. However, there are noticeable differences in education levels between the sample and the Canadian adult population, with the telephone sample being more educated than Census figures show. The largest gap was for the university educated stratum, with 49% of the sample having obtained a university degree, compared to 22% among Canadian adults. Education is a variable that could be considered in future weighting schemes for national surveys to correct for this imbalance. Income distributions for the sample are close to those measured in the 2016 Census. The country of birth distribution matches the 2016 Census.
Online sample
The online sample of 1,503 respondents was drawn from three online panels, including the Ipsos iSay panel, the MARU panel, and the Dynata panel. As this is a non-probability sample, a margin of error cannot be calculated. Respondents to the online survey were invited to participate via email, with a unique URL link to the survey provided to them. This link could only be used once, with respondents being allowed to take pause during completion and return to complete it at a later time. Survey questionnaires took 10 minutes to complete on average. All surveys were completed between August 28th and September 21st, 2020.
Incentives and quality control measures
Respondents to Ipsos’ online surveys are offered a number of innovative incentive programs in the forms of a point-based system where participants can redeem points for various items. We do not reward our panelists using cash payments.
Extensive quality-control procedures are in place within IIS (Ipsos Interactive Services, who manage our panel) to ensure that the survey inputs (sample and questionnaire design) allow for high-quality survey outputs (survey data). These processes span the life cycle of a panelist and are in place for all Ipsos online surveys. IIS experts are constantly monitoring and reviewing the performance of our quality measures and updating and integrating new ones as respondents’ behaviors and the online landscape evolve.
Panelists are who they say they are
· Double Opt-In approach to confirm identity
· Country validation via Geo-IP
· Mismatch between device settings and geolocation
· Anonymous proxy detection
· Detection of robots via Captcha code
· Detection of “5 minutes“ emails (temporary email addresses)
· Detection of data anomalies and patterns
· Maintenance of Ipsos blacklist
· RealAnswer™- detection of pasted and robot answers
They have not participated recently in similar surveys
· Strict panel usage rules to avoid interviewing the same people too often and prevent them from becoming too used to a type of survey or product category
· Duplicate devices identification through digital Fingerprinting (RelevantID®) and web/flashcookie
They complete surveys seriously
· Survey taking behavior: speeding, straight lining, open-ends quality evaluation
· Panelists’ history monitored across surveys and used for panel purge removing “bad” or inactive respondents
They can only take the survey once
· Duplicate emails identification
· Duplicate devices identification through digital fingerprinting (RelevantID®) and web/flashcookie
· Duplicate contact details identification
Online sample weighting
The tables below indicate the unweighted and weighted distributions of the online sample. The sample was stratified by region, with soft quotas also set for gender and age to ensure appropriate representation across categories. Weighting was applied to the sample to ensure that the final data reflects the adult population of Canada by region, age and gender according to the 2016 Census.
Please note, the totals below may not add up to 1,503 due to some respondents’ refusal to provide socioeconomic information.
Weighted and unweighted online sample: Region (Variable included in the weighting scheme)
|
|
Unweighted sample size |
Weighted sample size |
|
British Columbia/Territories |
197 |
209 |
|
Alberta |
165 |
168 |
|
Saskatchewan |
68 |
45 |
|
Manitoba |
70 |
52 |
|
ON |
529 |
575 |
|
QC |
342 |
351 |
|
Atlantic Canada |
132 |
103 |
Weighted and unweighted online sample: Gender (Variable included in the weighting scheme)
|
|
Unweighted sample size |
Weighted sample size |
|
Male |
726 |
725 |
|
Female |
767 |
767 |
|
Another gender |
4 |
6 |
Weighted and unweighted online sample: Age (Variable included in the weighting scheme)
|
|
Unweighted sample size |
Weighted sample size |
|
18-24 |
112 |
165 |
|
25-34 |
256 |
247 |
|
35-44 |
249 |
243 |
|
45-54 |
279 |
269 |
|
55-64 |
274 |
262 |
|
65+ |
333 |
317 |
Weighted and unweighted online sample: Education
|
|
Unweighted sample size |
Weighted sample size |
|
High school or less |
225 |
226 |
|
Some post-secondary |
120 |
129 |
|
Trade school or college |
447 |
441 |
|
University |
697 |
693 |
Weighted and unweighted online sample: Income
|
|
Unweighted sample size |
Weighted sample size |
|
Under $40K |
314 |
319 |
|
$40K to under $60K |
200 |
197 |
|
$60K to under $100K |
401 |
400 |
|
$100K or more |
377 |
371 |
Weighted and unweighted online sample: Country of birth
|
|
Unweighted sample size |
Weighted sample size |
|
Born in Canada |
1263 |
1254 |
|
Born outside of Canada |
232 |
240 |
Statistics presented in the tables above show minimal differences between the final unweighted and weighted samples. However, the youngest age group (18 to 24 years old) is underrepresented, resulting in a higher weight ratio of 1.37:1, which remains well within acceptable ranges for a survey of the general population and fares favourably compared to the gap observed in the telephone sample.
Email statistics
The table below presents general statistics regarding the response rate for the email phase of research.
|
Total |
|
|
32637 |
|
|
Invalid (incomplete/incorrect email address, email invitation bounce backs) |
0 |
|
Total unresolved units (no response at all) |
28435 |
|
Total in-scope - non-responding units |
223 |
|
Qualified respondent break-off (incomplete) |
223 |
|
Total in-scope - responding units |
3451 |
|
Over quota |
1831 |
|
Other disqualified |
119 |
|
Completed questionnaires |
1503 |
The response rate, calculated as the number of in-scope – responding units divided by the sum of unresolved units, in-scope – non-responding units, and in-scope – responding units, was 10.75%. This response rate is within normal ranges for a survey of the Canadian adult population.
Non-response analysis
As with any non-probability sample there exists within the current sample the possibility of non-response bias. In particular, this survey would not include members of the population who do not have access to a computer with an Internet connection (either at home or at work) or who are not capable of responding to a survey in either English or French. In addition, some groups within the population are systemically less likely to answer surveys.
The tables below compare the unweighted sample to the 2016 Census results by region, age, gender, education, income and country of birth. Overall, the sample is highly representative of the national adult population, except for a few gaps which are described below.
Online sample population comparison: Region (Variable included in the weighting scheme)
|
|
Unweighted percentage |
Census 2016 proportions (adults) |
|
British Columbia/Territories |
13% |
14% |
|
Alberta |
11% |
11% |
|
Saskatchewan |
5% |
3% |
|
Manitoba |
5% |
4% |
|
ON |
35% |
38% |
|
QC |
23% |
24% |
|
Atlantic Canada |
9% |
7% |
Online sample population comparison: Gender (Variable included in the weighting scheme)
|
|
Unweighted percentage |
Census 2016 proportions (adults) |
|
Male |
48% |
49% |
|
Female |
51% |
51% |
Online sample population comparison: Age (Variable included in the weighting scheme)
|
|
Unweighted percentage |
Census 2016 proportions (adults) |
|
18-24 |
7% |
11% |
|
25-34 |
17% |
16% |
|
35-44 |
17% |
16% |
|
45-54 |
19% |
18% |
|
55-64 |
18% |
18% |
|
65+ |
22% |
21% |
Online sample population comparison: Education
|
|
Unweighted percentage |
Census 2016 proportions (adults) |
|
High school or less |
23% |
43% |
|
Trade school or college |
30% |
35% |
|
University or higher |
46% |
22% |
Online sample population comparison: Income
|
|
Unweighted percentage |
Census 2016 proportions (adults) |
|
Under $40K |
21% |
26% |
|
$40K to under $60K |
13% |
16% |
|
$60K to under $100K |
27% |
25% |
|
$100K or more |
25% |
32% |
Online sample population comparison: Country of birth
|
|
Unweighted percentage |
Census 2016 proportions (adults) |
|
Born in Canada |
84% |
78% |
|
Born outside of Canada |
15% |
22% |
The comparison for the variables used in the weighting scheme are minimal, except for a small gap for the youngest age group, which is slightly underrepresented in the unweighted sample. However, as discussed above, the age distribution in the online sample remains solid. The largest observable gaps between the unweighted sample and Census 2016 data relates to education levels, as observed with the phone sample as well. We find that the unweighted sample tends to overrepresented more educated Canadians, although the gaps are not as high as in the telephone sample. The online sample also contains a smaller proportion of Canadians who have a household income of $100,000 and above, as well as a slightly smaller proportion of immigrants.
Comparison of phone and online samples
The tables below present a comparison of the telephone and online samples across the variables used in the weighting scheme for samples. Totals for each variable may not add up to total sample size due to some respondents’ refusal to provide socioeconomic information.
Telephone and online sample comparison: Region (Variable included in the weighting scheme)
|
|
Unweighted phone sample |
Unweighted online sample |
|
British Columbia/Territories |
13% |
13% |
|
Alberta |
10% |
11% |
|
Saskatchewan |
7% |
5% |
|
Manitoba |
7% |
5% |
|
ON |
32% |
35% |
|
QC |
22% |
23% |
|
Atlantic Canada |
10% |
9% |
Telephone and online sample comparison: Gender (Variable included in the weighting scheme)
|
|
Unweighted phone sample |
Unweighted online sample |
|
Male |
48% |
48% |
|
Female |
51% |
51% |
Telephone and online sample comparison: Age (Variable included in the weighting scheme)
|
|
Unweighted phone sample |
Unweighted online sample |
|
18-24 |
8% |
7% |
|
25-34 |
14% |
17% |
|
35-44 |
18% |
17% |
|
45-54 |
18% |
19% |
|
55-64 |
20% |
18% |
|
65+ |
23% |
22% |
Comparison by socioeconomic information not used in weighting
The next tables show the comparison between both samples for education and income levels, as well as country of birth, which were not included in the weighting scheme. Considering that no quotas were set for any of these three variables during fieldwork, the similarities between the two samples are remarkable. As discussed above, both samples over represent university-educated Canadians and underrepresent those with a completed high school degree or less. Some differences can also be seen with regards to income levels when comparing the online and phone respondents. More specifically, these gaps are visible in the under $40,000 bracket (4-point gap) and the $100,000 or more bracket (10-point gap).
Finally, both samples show a difference in the proportion of respondents born in Canada. While 23% of phone respondents report being born outside of the country, only 15% of online respondents report the same. According to Census 2016 figures, the actual proportion in the Canadian population is 22%. Therefore, the telephone sample very closely represents the immigrant population, while the online sample slightly underrepresents it.
Telephone and online sample comparison: Education
The breakdown for education shown here is slightly different from that shown in
tables above in order to match the data description used for Census 2016.
|
|
Unweighted phone sample |
Unweighted online sample |
Census 2016 |
|
High school or less |
24% |
23% |
43% |
|
Trade school or college |
26% |
30% |
35% |
|
University |
49% |
46% |
22% |
Telephone and online sample comparison: Income
|
|
Unweighted phone sample |
Unweighted online sample |
Census 2016 |
|
Under $40K |
17% |
21% |
26% |
|
$40K to under $60K |
13% |
13% |
16% |
|
$60K to under $100K |
26% |
27% |
25% |
|
$100K or more |
35% |
25% |
33% |
Telephone and online sample comparison: Country of birth
|
|
Unweighted phone sample |
Unweighted online sample |
Census 2016 |
|
Born in Canada |
77% |
84% |
78% |
|
Born outside of Canada |
23% |
15% |
22% |
The differences noted above in the proportion of immigrants sampled via each mode of interviewing do not explain some of the statistical differences noted in survey responses from one data collection mode to the other. Respondents who are not born in Canada are more positive than those born in the country on most questions included in this study, but the size of those gaps in attitudes are too small to make the kind of difference that would be needed to explain the differences in survey responses between online and phone respondents.
Appendix 2 – Quantitative methodology (Wave 2)
Telephone survey
Ipsos conducted a 15-minute telephone survey among a nationwide sample of n=1,501 Canadian adults between February 18th and March 10th, 2021. The sample is a probability sample generated through random digit dialing. For respondents contacted on a landline, respondents within households were selected at random, by using the “birthday method” of identifying and interviewing the member of the household (aged 18+) who had their birthday last.
Respondents contacted on a cellular phone were also random digit dialed, and needed to be 18+ to participate. Wireless samples were selected on a provincial level (as it is not practical to accurately select by market given the mobile nature of the technology) from a database containing all possible numbers in 1000-blocks of area codes and exchanges dedicated to wireless numbers.
Within the total sample of 1,501 Canadians for this survey, 451 respondents were contacted on their landlines, while the other 1,050 respondents were contacted on their cellphones. The margin of error for a telephone survey of 1,501 respondents is ±2.5%, using a confidence interval of 95% (19 times out of 20). The final questionnaire used was provided by IRCC to ensure adequate tracking of previous research results conducted by the department.
Telephone sample weighting
The tables below indicate the unweighted and weighted distributions of the telephone sample. The sample was stratified by region, with soft quotas also set for gender and age to ensure appropriate representation across categories. Weighting was applied to the sample to ensure that the final data reflects the adult population of Canada by region, age and gender according to the 2016 Census.
Please note, the totals below may not add up to 1,501 due to some respondents’ refusal to provide socioeconomic information.
Weighted and unweighted telephone sample: Region (Variable included in the weighting scheme)
|
|
Unweighted sample size |
Weighted sample size |
|
British Columbia/Territories |
190 |
207 |
|
Alberta |
155 |
167 |
|
Saskatchewan |
100 |
45 |
|
Manitoba |
101 |
52 |
|
ON |
480 |
571 |
|
QC |
325 |
356 |
|
Atlantic Canada |
150 |
103 |
Weighted and unweighted telephone sample: Gender (Variable included in the weighting scheme)
|
|
Unweighted sample size |
Weighted sample size |
|
Male |
733 |
723 |
|
Female |
747 |
765 |
|
Another gender |
11 |
5 |
Weighted and unweighted telephone sample: Age (Variable included in the weighting scheme)
|
|
Unweighted sample size |
Weighted sample size |
|
18-24 |
130 |
164 |
|
25-34 |
185 |
246 |
|
35-44 |
241 |
242 |
|
45-54 |
289 |
269 |
|
55-64 |
273 |
262 |
|
65+ |
383 |
317 |
Weighted and unweighted telephone sample: Education
|
|
Unweighted sample size |
Weighted sample size |
|
High school or less |
240 |
230 |
|
Some post-secondary |
132 |
129 |
|
Trade school or college |
433 |
438 |
|
University |
683 |
692 |
Weighted and unweighted telephone sample: Income
|
|
Unweighted sample size |
Weighted sample size |
|
Under $40K |
312 |
312 |
|
$40K to under $60K |
214 |
206 |
|
$60K to under $100K |
390 |
392 |
|
$100K or more |
490 |
501 |
Weighted and unweighted telephone sample: Country of birth
|
|
Unweighted sample size |
Weighted sample size |
|
Born in Canada |
1142 |
1115 |
|
Born outside of Canada |
357 |
383 |
Statistics presented in the table above show minimal differences between the final unweighted and weighted samples. However, the youngest age group (18 to 24 years old) is underrepresented, resulting in a higher unweighted to weighted ratio.
Call dispositions
The following table provides the call dispositions and response rate calculation, as per the former MRIA’s empirical method of calculating response rates for telephone surveys.
|
Landline |
Cellphone |
Total |
|
|
Total Numbers Attempted |
26169 |
13994 |
40163 |
|
Invalid (NIS, fax/modem, business/non-res.) |
16718 |
8609 |
25327 |
|
Total unresolved units (Busy, no answer, answering machine) |
4744 |
2450 |
7194 |
|
Total in-scope - non-responding units |
3647 |
2419 |
6066 |
|
Language problem |
90 |
25 |
115 |
|
Illness, incapable, deaf |
50 |
7 |
57 |
|
Household refusal |
3468 |
2369 |
5837 |
|
Qualified respondent break-off |
39 |
18 |
57 |
|
Total in-scope - responding units |
557 |
1071 |
1628 |
|
Over quota |
105 |
2 |
107 |
|
No one 18+ |
1 |
19 |
20 |
|
Occupation Disqualified |
0 |
0 |
0 |
|
Completed interviews |
451 |
1050 |
1501 |
The response rate, calculated as the number of in-scope – responding units divided by the sum of unresolved units, in-scope – non-responding units, and in-scope – responding units, was 6.22% for landline numbers, 18.03% for cellphone numbers, and 10.93% for all telephone numbers. The total response rate of 10.93% for a telephone survey of the Canadian general population with up to 8 call-backs per household is typical.
Non-response analysis
As with any probability sample, there exists within the current sample the possibility of non-response bias. In particular, this survey would not include members of the population who do not have access to a telephone (either landline or cell phone) or who are not capable of responding to a survey in either English or French. In addition, some groups within the population are systemically less likely to answer surveys.
The table below compares the unweighted sample to the 2016 Census results by region, age, gender, education, income and country of birth. The comparison between the two samples for the three variables used in the weighting scheme (using interlocking weights for region with age and region with gender) shows a slight underrepresentation of younger Canadians (18 to 24 years of age). However, this discrepancy is small enough that it can be corrected through weighting without affecting the quality of the final results. As the regional distribution was set through hard quotas, the weighting had virtually no impact on final numbers.
Telephone sample population comparison: Region (Variable included in the weighting scheme)
|
|
Unweighted percentage |
Census 2016 proportions (adults) |
|
British Columbia/Territories |
13% |
14% |
|
Alberta |
10% |
11% |
|
Saskatchewan |
7% |
3% |
|
Manitoba |
7% |
4% |
|
ON |
32% |
38% |
|
QC |
22% |
24% |
|
Atlantic Canada |
10% |
7% |
Telephone sample population comparison: Gender (Variable included in the weighting scheme)
|
|
Unweighted percentage |
Census 2016 proportions (adults) |
|
Male |
49% |
49% |
|
Female |
50% |
51% |
Telephone sample population comparison: Age (Variable included in the weighting scheme)
|
|
Unweighted percentage |
Census 2016 proportions (adults) |
|
18-24 |
9% |
11% |
|
25-34 |
12% |
16% |
|
35-44 |
16% |
16% |
|
45-54 |
19% |
18% |
|
55-64 |
18% |
18% |
|
65+ |
26% |
21% |
Telephone sample population comparison: Education
|
|
Unweighted percentage |
Census 2016 proportions (adults) |
|
High school or less |
16% |
43% |
|
Trade school or college |
38% |
35% |
|
University or higher |
46% |
22% |
Telephone sample population comparison: Income
|
|
Unweighted percentage |
Census 2016 proportions (adults) |
|
Under $40K |
21% |
26% |
|
$40K to under $60K |
14% |
16% |
|
$60K to under $100K |
26% |
25% |
|
$100K or more |
33% |
32% |
Telephone sample population comparison: Country of birth
|
|
Unweighted percentage |
Census 2016 proportions (adults) |
|
Born in Canada |
76% |
78% |
|
Born outside of Canada |
24% |
22% |
This comparison between the unweighted sample distribution and the actual population figures for variables not included in the weighting scheme shows that the final sample obtained was mostly representative of the general population for this survey. However, there are noticeable differences in education levels between the sample and the Canadian adult population, with the telephone sample being more educated than Census figures show. The largest gap was for the university educated stratum, with 46% of the sample having obtained a university degree, compared to 22% among Canadian adults. Education is a variable that could be considered in future weighting schemes for national surveys to correct for this imbalance. Income distributions for the sample are close to those measured in the 2016 Census. The country of birth distribution matches the 2016 Census.
Online sample
The online sample of 1,500 respondents was drawn from three online panels, including the Ipsos iSay panel, the MARU panel, and the Dynata panel. As this is a non-probability sample, a margin of error cannot be calculated. Respondents to the online survey were invited to participate via email, with a unique URL link to the survey provided to them. This link could only be used once, with respondents being allowed to take pause during completion and return to complete it at a later time. Survey questionnaires took 14 minutes to complete on average. All surveys were completed between February 26th and March 10th, 2021.
Incentives and quality control measures
Respondents to Ipsos’ online surveys are offered a number of innovative incentive programs in the forms of a point-based system where participants can redeem points for various items. We do not reward our panelists using cash payments.
Extensive quality-control procedures are in place within IIS (Ipsos Interactive Services, who manage our panel) to ensure that the survey inputs (sample and questionnaire design) allow for high-quality survey outputs (survey data). These processes span the life cycle of a panelist and are in place for all Ipsos online surveys. IIS experts are constantly monitoring and reviewing the performance of our quality measures and updating and integrating new ones as respondents’ behaviors and the online landscape evolve.
Panelists are who they say they are
· Double Opt-In approach to confirm identity
· Country validation via Geo-IP
· Mismatch between device settings and geolocation
· Anonymous proxy detection
· Detection of robots via Captcha code
· Detection of “5 minutes“ emails (temporary email addresses)
· Detection of data anomalies and patterns
· Maintenance of Ipsos blacklist
· RealAnswer™- detection of pasted and robot answers
They have not participated recently in similar surveys
· Strict panel usage rules to avoid interviewing the same people too often and prevent them from becoming too used to a type of survey or product category
· Duplicate devices identification through digital Fingerprinting (RelevantID®) and web/flashcookie
They complete surveys seriously
· Survey taking behavior: speeding, straight lining, open-ends quality evaluation
· Panelists’ history monitored across surveys and used for panel purge removing “bad” or inactive respondents
They can only take the survey once
· Duplicate emails identification
· Duplicate devices identification through digital fingerprinting (RelevantID®) and web/flashcookie
· Duplicate contact details identification
Online sample weighting
The tables below indicate the unweighted and weighted distributions of the online sample. The sample was stratified by region, with soft quotas also set for gender and age to ensure appropriate representation across categories. Weighting was applied to the sample to ensure that the final data reflects the adult population of Canada by region, age and gender according to the 2016 Census.
Please note, the totals below may not add up to 1,500 due to some respondents’ refusal to provide socioeconomic information.
Weighted and unweighted online sample: Region (Variable included in the weighting scheme)
|
|
Unweighted sample size |
Weighted sample size |
|
British Columbia/Territories |
184 |
205 |
|
Alberta |
156 |
166 |
|
Saskatchewan |
100 |
45 |
|
Manitoba |
100 |
54 |
|
ON |
482 |
577 |
|
QC |
327 |
350 |
|
Atlantic Canada |
150 |
101 |
Weighted and unweighted online sample: Gender (Variable included in the weighting scheme)
|
|
Unweighted sample size |
Weighted sample size |
|
Male |
723 |
723 |
|
Female |
767 |
766 |
|
Another gender |
7 |
6 |
Weighted and unweighted online sample: Age (Variable included in the weighting scheme)
|
|
Unweighted sample size |
Weighted sample size |
|
18-24 |
97 |
164 |
|
25-34 |
267 |
246 |
|
35-44 |
258 |
242 |
|
45-54 |
279 |
269 |
|
55-64 |
272 |
262 |
|
65+ |
327 |
316 |
Weighted and unweighted online sample: Education
|
|
Unweighted sample size |
Weighted sample size |
|
High school or less |
193 |
197 |
|
Some post-secondary |
134 |
140 |
|
Trade school or college |
446 |
433 |
|
University |
707 |
717 |
Weighted and unweighted online sample: Income
|
|
Unweighted sample size |
Weighted sample size |
|
Under $40K |
312 |
307 |
|
$40K to under $60K |
248 |
251 |
|
$60K to under $100K |
397 |
386 |
|
$100K or more |
360 |
357 |
Weighted and unweighted online sample: Country of birth
|
|
Unweighted sample size |
Weighted sample size |
|
Born in Canada |
1233 |
1214 |
|
Born outside of Canada |
261 |
279 |
Statistics presented in the tables above show minimal differences between the final unweighted and weighted samples. However, the youngest age group (18 to 24 years old) is underrepresented, resulting in a higher weight ratio of 1.83:1, which remains well within acceptable ranges for a survey of the general population and fares favourably compared to the gap observed in the telephone sample.
Email statistics
The table below presents general statistics regarding the response rate for the email phase of research.
|
Total |
|
|
Total Email Invitations Issued |
28506 |
|
Invalid (incomplete/incorrect email address, email invitation bounce backs) |
0 |
|
Total unresolved units (no response at all) |
24835 |
|
Total in-scope - non-responding units |
283 |
|
Qualified respondent break-off (incomplete) |
283 |
|
Total in-scope - responding units |
3388 |
|
Over quota |
1756 |
|
Other disqualified |
132 |
|
Completed questionnaires |
1500 |
The response rate, calculated as the number of in-scope – responding units divided by the sum of unresolved units, in-scope – non-responding units, and in-scope – responding units, was 11.89%. This response rate is within normal ranges for a survey of the Canadian adult population.
Non-response analysis
As with any non-probability sample there exists within the current sample the possibility of non-response bias. In particular, this survey would not include members of the population who do not have access to a computer with an Internet connection (either at home or at work) or who are not capable of responding to a survey in either English or French. In addition, some groups within the population are systemically less likely to answer surveys.
The tables below compare the unweighted sample to the 2016 Census results by region, age, gender, education, income and country of birth. Overall, the sample is highly representative of the national adult population, except for a few gaps which are described below.
Online sample population comparison: Region (Variable included in the weighting scheme)
|
|
Unweighted percentage |
Census 2016 proportions (adults) |
|
British Columbia/Territories |
12% |
14% |
|
Alberta |
10% |
11% |
|
Saskatchewan |
7% |
3% |
|
Manitoba |
7% |
4% |
|
ON |
32% |
38% |
|
QC |
22% |
24% |
|
Atlantic Canada |
10% |
7% |
Online sample population comparison: Gender (Variable included in the weighting scheme)
|
|
Unweighted percentage |
Census 2016 proportions (adults) |
|
Male |
48% |
49% |
|
Female |
51% |
51% |
Online sample population comparison: Age (Variable included in the weighting scheme)
|
|
Unweighted percentage |
Census 2016 proportions (adults) |
|
18-24 |
6% |
11% |
|
25-34 |
18% |
16% |
|
35-44 |
17% |
16% |
|
45-54 |
19% |
18% |
|
55-64 |
18% |
18% |
|
65+ |
22% |
21% |
Online sample population comparison: Education
|
|
Unweighted percentage |
Census 2016 proportions (adults) |
|
High school or less |
32% |
43% |
|
Trade school or college |
43% |
35% |
|
University or higher |
23% |
22% |
Online sample population comparison: Income
|
|
Unweighted percentage |
Census 2016 proportions (adults) |
|
Under $40K |
21% |
26% |
|
$40K to under $60K |
17% |
16% |
|
$60K to under $100K |
26% |
25% |
|
$100K or more |
24% |
32% |
Online sample population comparison: Country of birth
|
|
Unweighted percentage |
Census 2016 proportions (adults) |
|
Born in Canada |
82% |
78% |
|
Born outside of Canada |
17% |
22% |
The comparison for the variables used in the weighting scheme are minimal, except for a small gap for the youngest age group, which is slightly underrepresented in the unweighted sample. However, as discussed above, the age distribution in the online sample remains solid. The largest observable gaps between the unweighted sample and Census 2016 data relates to education levels, as observed with the phone sample as well. We find that the unweighted sample tends to overrepresented more educated Canadians, although the gaps are not as high as in the telephone sample. The online sample also contains a smaller proportion of Canadians who have a household income of $100,000 and above, as well as a slightly smaller proportion of immigrants.
Comparison of phone and online samples
The tables below present a comparison of the telephone and online samples across the variables used in the weighting scheme for samples. Totals for each variable may not add up to total sample size due to some respondents’ refusal to provide socioeconomic information.
Telephone and online sample comparison: Region (Variable included in the weighting scheme)
|
|
Unweighted phone sample |
Unweighted online sample |
|
British Columbia/Territories |
13% |
12% |
|
Alberta |
10% |
10% |
|
Saskatchewan |
7% |
7% |
|
Manitoba |
7% |
7% |
|
ON |
32% |
32% |
|
QC |
22% |
22% |
|
Atlantic Canada |
10% |
10% |
Telephone and online sample comparison: Gender (Variable included in the weighting scheme)
|
|
Unweighted phone sample |
Unweighted online sample |
|
Male |
49% |
48% |
|
Female |
50% |
51% |
Telephone and online sample comparison: Age (Variable included in the weighting scheme)
|
|
Unweighted phone sample |
Unweighted online sample |
|
18-24 |
9% |
6% |
|
25-34 |
12% |
18% |
|
35-44 |
16% |
17% |
|
45-54 |
19% |
19% |
|
55-64 |
18% |
18% |
|
65+ |
26% |
22% |
Comparison by socioeconomic information not used in weighting
The next tables show the comparison between both samples for education and income levels, as well as country of birth, which were not included in the weighting scheme. Considering that no quotas were set for any of these three variables during fieldwork, the similarities between the two samples are remarkable. As discussed above, both samples over represent educated Canadians and underrepresent those with a completed high school degree or less. Some differences can also be seen with regards to income levels when comparing the online and phone respondents. More specifically, these gaps are visible in the $100,000 or more bracket (9-point gap).
Finally, both samples show a difference in the proportion of respondents born in Canada. While 24% of phone respondents report being born outside of the country, only 17% of online respondents report the same. According to Census 2016 figures, the actual proportion in the Canadian population is 22%. Therefore, the telephone sample very closely represents the immigrant population, while the online sample slightly underrepresents it.
Telephone and online sample comparison: Education
The breakdown for education shown here is slightly different from that shown in
tables above in order to match the data description used for Census 2016.
|
|
Unweighted phone sample |
Unweighted online sample |
Census 2016 |
|
High school or less |
16% |
32% |
43% |
|
Trade school or college |
38% |
43% |
35% |
|
University |
46% |
23% |
22% |
Telephone and online sample comparison: Income
|
|
Unweighted phone sample |
Unweighted online sample |
Census 2016 |
|
Under $40K |
21% |
21% |
26% |
|
$40K to under $60K |
14% |
17% |
16% |
|
$60K to under $100K |
26% |
26% |
25% |
|
$100K or more |
33% |
24% |
33% |
Telephone and online sample comparison: Country of birth
|
|
Unweighted phone sample |
Unweighted online sample |
Census 2016 |
|
Born in Canada |
76% |
82% |
78% |
|
Born outside of Canada |
24% |
17% |
22% |
The differences noted above in the proportion of immigrants sampled via each mode of interviewing do not explain some of the statistical differences noted in survey responses from one data collection mode to the other. Respondents who are not born in Canada are more positive than those born in the country on most questions included in this study, but the size of those gaps in attitudes are too small to make the kind of difference that would be needed to explain the differences in survey responses between online and phone respondents.
Appendix 3 – Qualitative and quantitative instruments
English and French qualitative and quantitative instruments are provided under separate cover.