CANSSI EDI

This document is abstracted from the CANSSI application to the DIS program.

CANSSI EDI is a catalyst and laboratory for policies, programs, training, and
activities addressing equity, diversity, and inclusion in Canadian statistical sciences.

From the outset, CANSSI’s research orientation and dedication to supporting all statistical scientists across Canada led to close alignment with important aspects of Equity, Diversity and Inclusion (EDI), specifically:

Diversity is key to forming the strongest and most effective research collaborations.
Equity is key to enabling all members of a collaboration to reach their potential.
Inclusion is key to successful collaborations and maximizing individual success.

CANSSI EDI is a comprehensive, multi-dimensional approach to EDI that has evolved from the Institute’s longstanding commitment to EDI. CANSSI EDI occupies a special place in CANSSI programming because diversity is a sine qua non of collaborative and interdisciplinary research [2,3, 4,5,8,9,10,11,14,21,33,38,40,48]. The success of CANSSI EDI is therefore key to the success of all the other CANSSI Flagship programs. For this reason, CANSSI EDI is a living program that is updated continuously as we evaluate our activities, acquire new experience and data, and adapt to changes in society. The Discovery Institutes Support (DIS) program provides the opportunity to implement a comprehensive EDI program that has the potential to have real impact.

1 Background

Under the Collaborative and Thematic Resources Support in Mathematics and Statistics (CTRMS) program [13], CANSSI’s efforts in EDI were framed by the experiences and commitment of first two Scientific Directors (SDs) (Professors Mary Thompson and Nancy Reid) and by requirements for EDI from NSERC and universities during this period [13,46,59]. The scope was defined by the focus of CANSSI on the CRT program and dealt with EDI issues related to that program. Specifically, CANSSI has always used evaluation processes and criteria that avoid common biases in academic adjudication processes [22,23,24,25,26,27,28,38,46]. The result is a sustained history of strong diversity in project leadership and supported HQP as well as geographic and institutional heterogeneity in CRT projects. In addition, CANSSI has a sustained history of strong diversity in its leadership committees.

There has been significant evolution in the view of EDI among funding agencies, universities, and research communities since the CTRMS competition in 2013 [47,60,61]. This includes a re-assessment of the complexity of EDI, the myriad ways that EDI issues impact training and research, and the expectation that EDI will be integrated into research and training. In response, CANSSI has evolved its earlier EDI activities into a comprehensive, multidimensional EDI program called CANSSI EDI that is focused on developing specific actions to tackle barriers, challenges, inequities, bias, and lack of inclusivity that affect underrepresented and disadvantaged populations. This orientation provides a systematic way to identify specific challenges, develop strategies and plans, and devise metrics for evaluation of results.

2 CANSSI EDI

CANSSI EDI is modeled after the EDI framework of the New Frontiers in Research Program [60]. The dimensions of CANSSI EDI include Policy, Education and Training, Support for Inclusion and Accessibility, Outreach and Expansion, and Measurement and Evaluation. The policies, programs and activities are guided by the CANSSI EDI Committee which includes the SSC EDI Committee and CANSSI appointed members. SD Estep has discussed EDI activities that can be supported by NSERC and the need to navigate national and provincial laws related to EDI with NSERC several times. We describe the components briefly.

Policy: CANSSI’s EDI policies and requirements include:

Policies related to governance and operations of the institute, diversity standards for selection of SD and DD, committee members and staff, and adjudication processes for scientific programs.

Requirements for CANSSI-supported researchers and HQP, including participation in CANSSI EDI programming and incorporating consideration of EDI into their research and training programs.
Advisory relationships with individuals and companies with expertise in EDI.
Continuing CANSSI’s strong grass-roots tradition by including the Canadian statistical sciences community in the evaluation and guidance of CANSSI EDI.

Education and Training: CANSSI provides training in EDI through a dynamic program of events and training courses. The goal is to strengthen the engagement with EDI in the community and develop future leaders committed to pursuing EDI in their research and training activities. Activities include:

Seminars, workshops, and other activities concerned with EDI issues. For example, CANSSI sponsored a national showing of the film “Picture a Scientist” and a panel discussion in May, 2021.
Panels and national townhalls on EDI issues. For example, in Fall 2021 CANSSI and the SSC sponsored the CANSSI National Townhall on Mentoring and Networks. In Spring 2022, CANSSI, PIMS, CRM and AARMS will organize a townhall on the biases in student teaching evaluations.
EDI training courses offered by professional organizations specializing in EDI. For example, in Fall 2021, CANSSI sponsored “Diversity and Inclusion Fundamentals” taught by the Canadian Centre for Diversity and Inclusion (CCDI) [61]. We will work with such organizations to develop a training library that is relevant to mathematical and statistical sciences. A committee appointed by CANSSI and PIMS are working with CCDI to evolve the first course. The plan is to offer at least four training courses per year using several companies. Some of the courses will be part of sequences.
CANSSI provides supportive opportunities, e.g., the CANSSI Showcase, for young researchers and HQP to share their research with the community while honing their communication skills.

Support for Inclusion and Accessibility: CANSSI provides professional support and opportunities for HQP and researchers aimed at building inclusivity and accessibility:

By design, CANSSI programs encourage partnerships among researchers at different institutions, appointments, career stages, and regions of Canada. There is strong evidence that this strengthens inclusivity and accessibility in CANSSI-supported activities.
CANSSI provides professional mentoring, training in communication of research, and support for applications to CANSSI programs. We are expanding the mentoring programs based on community input from the CANSSI National Townhall on Mentoring and Networks, especially on EDI issues.
By design, the GSES program is accessible to junior researchers at any university and provides valuable professional and mentoring experience.
By design, the RSG program supports researchers and HQP interested in applied research with a direct impact on problems important to society, thus supporting areas that are often underfunded compared to other areas of scientific research [9,10,19,25,26,27,28,32,44,51].
The CDPF and CRT programs provide an opportunity for faculty to establish prominent research leadership. Paired with the sustained record for strong diversity in CRT and CDPF leads, the consequence is visible evidence that faculty from underrepresented and disadvantaged groups are successful in CANSSI programs.

Outreach and expansion: CANSSI undertakes activities directed towards increasing diversity in the statistical sciences community. A critical issue is increasing the number of students from underrepresented and disadvantaged groups that consider statistics in their future. The challenges begin at the secondary level, since little statistics is covered in standard curriculums, few teachers are trained in statistics, and the advantages that statistical training conveys for career paths is often unknown. The challenges continue in postsecondary education, e.g., the range of statistics courses is small, statistics is often taught by non-statisticians, and there is no opportunity for statistics research in colleges and smaller universities, which often serve relatively large disadvantaged and underrepresented groups.

Outreach and expansion activities in CANSSI’s portfolio are designed to meet specific challenges. The degree to which the costs of the major activities can be supported through the DIS program, the strength and number of partnerships with other organizations required, and the time scale for implementation varies significantly across the activities. In more complex cases, the strategy is to initiate each activity to the extent that is allowable within NSERC support followed by building a coalition of partners that can undertake implementation of the full activity.

CANSSI supports activities designed to reach postsecondary students who have a relatively strong quantitative background. For example, we support the Vancouver Datajam, Hockey Hackathon, and summer training camps which make a concerted effort to reach underrepresented and disadvantaged groups and operate programs designed to create inclusive environments. Another example is the International Day of Women and Girls in Science, that CANSSI Ontario organized in February 2021, which spotlighted women researchers in Ontario by streaming profiles of 54 scientists on social media and web pages. These kinds of activities can have a strongly positive impact on individuals, but their short time scale, small participant numbers, and narrow scope blunt the potential for significant broad impact.

In a much more significant development, CANSSI is a major co-sponsor and co-organizer of the Florence Nightingale Day (FND) together with the Caucus for Women in Statistics (CWS) and the American Statistical Association (ASA). Operating since 2018, the FND is an international one-day event aimed at attracting secondary students from underrepresented and disadvantaged groups to study statistical sciences. The FND includes panels with strong diversity in composition including university students, faculty and industry researchers and hands-on statistics activities led by students, faculty, and high school teachers. The FND is organized at local colleges and universities for high school students from the region and virtually for students from all over the world. SD Estep serves on the Board of Directors of Florence Nightingale Day, Inc. and CANSSI underwrites a significant portion of the costs. The vision is to expand FND to become a national event involving high school students across Canada. This involves using university offices and national organizations to build ties to local school boards, especially those working with large underrepresented and disadvantaged populations. We will explore the feasibility of sending students and faculty to remote institutions to support FND as well as increasing access by individual students. We also want to move the event to a school day to decrease the financial barrier associated with weekend activities. In addition to supporting the annual FND, CANSSI is helping teams at Simon Fraser University (SFU) and U. Toronto organize Canadian-focused offerings in February as test cases. The goal is to have several Canadian universities take part in the annual FND in October 2022 and grow from there.

We briefly describe two ambitious, long-term activities that CANSSI is initiating. Based on fundability discussions with NSERC, we do not request support for these activities in the DIS budget. However, we were encouraged to provide brief descriptions. Further details are provided in the references.

CANSSI is initiating elements of the CANSSI Research Training Library (CRTL) [54] that houses high quality sets of materials for research-level courses in order to provide students at all Canadian universities and colleges access to advanced preparation for research. The concept of the CRTL was developed at the National Retreat in 2020 and is one of the most frequent requests for new programs that CANSSI receives. It is motivated by the fact that students at some resource-constrained universities have limited access to research-level coursework, which affects their preparation for future careers and competitiveness in seeking employment. Moreover, the pressures of exploding enrollments (§II.1) means that most departments have need for the program.

CANSSI is also initiating components of the SURMOUNT [62] program, which takes inspiration from US National Science Foundation (NSF) programs and collaborations between US universities and minority-serving institutions, SURMOUNT aims to create partnerships that serve cohorts of students in statistical sciences from disadvantaged and underrepresented groups. It provides access to advanced courses, research opportunities, and mentoring that can prepare students for success in graduate school while directly reducing the host of socio-economic barriers they routinely face. SURMOUNT depends on creating a partnership between universities, government agencies and industry. Institutes like CANSSI have a key role in the program.

All of CANSSI outreach activities are supported by a comprehensive communication action plan that disseminates opportunities to participate, showcases accomplishments of the diverse community involved with CANSSI programs and includes personal outreach by the SD and DD to universities in Canada.

Measurement and Evaluation:To evaluate the effectiveness and impact of CANSSI EDI policies and activities, CANSSI employs a comprehensive approach, including

A comprehensive effort to collect diversity data on participants, leaders, and supervisors as well as adjudication processes for all of CANSSI programs.
Organizing an annual townhall on EDI activities of CANSSI to gather community feedback.
Working with professional organizations and consultants to rigorously evaluate CANSSI EDI as well as CANSSI operations under the guidance of a sub-committee of the Board of Directors (BoD).

3 Diversity data

We present demographic data on diversity in past CANSSI operations to provide context for CANSSI EDI. First, we make some observations on diversity data collection in Canada and describe CANSSI’s past efforts. The recognition of the importance of collecting diversity data and understanding of how diversity should be quantified has changed dramatically and frequently during the CTRMS era. A well-recognized issue in Canada is that low response rates imply data from self-identification surveys are problematic, and conclusions drawn from such data involve significant uncertainty. Finally, there are numerous national and provincial privacy laws restricting the use of diversity data.

Up until 2020, CANSSI asked organizers of workshops and such events to distribute a sex identification survey to participants. At the same time, the professional details of every individual involved with a CRT or PDF were recorded in CANSSI’s annual NSERC and public reports, while the SD knew all project leads/supervisors and many of the collaborators and HQP in statistical sciences personally. Thus, CANSSI never requested self-identification data nor permission to use diversity data from that group. As part of planning for new programs, CANSSI conducted a forensic evaluation of diversity by inspection of the public data assisted by project leads but did not get self-identification data or permissions from many people involved in Flagship programs over seven years.

Increasing efforts to collect demographic data is an important component of CANSSI EDI. Recognizing deficiencies in data collection, CANSSI introduced an internally managed comprehensive self-identification demographic survey in 2020 for workshops and other events. In 2021, we began using the self-identification survey for all CANSSI programs.

With this background, we present data, starting with self-identification data for governance committees. The current BoD is comprised of 42% female and 42% Black, Indigenous, People of Color (BIPOC) members. The cumulative data are 29% female and 26% BIPOC members. The Scientific Advisory Committee (SAC) is currently comprised of 90% female and 33% BIPOC members. The cumulative data are 42% female and 23% BIPOC members.

Using self-identification surveys in workshops, conferences, datathons, and summer schools, we obtained 41% respondents self-identifying as female.

As explained, we cannot report precise data for Flagship programs even though personal information of researchers and HQP is recorded in the public and NSERC annual reports. In summary, well over half of the 23 CRT projects have at least one female lead and around half have at least one BIPOC lead. Of the total personnel, roughly a third of the team members are female and a third are BIPOC. The RSG and CDPF data are similar. We have not supported a lead or HQP that self-identifies as Indigenous. We note the diversity of supported HQP in Flagship programs is significantly lower than the diversity of the leads.

4 Impact on users

CANSSI programs have a very significant impact on the advancement of research programs of project leads and supervisors and the research careers of HQP. The reason is that CANSSI programs provide support for collaborative and interdisciplinary research activities together with associated training opportunities that cannot be supported by other funding programs, e.g., DGP. The impact of CANSSI support on the research programs of researchers is documented in the productivity data.

CANSSI’s emphasis on sustained collaborations and interdisciplinary research, and on the training of HQP in interdisciplinary research, has helped to invigorate research in statistical sciences across the country. It has changed the culture of how statisticians see their role in research, from helpers to equal partners. It has created excitement and enthusiasm for new opportunities. It has literally opened the floodgates for new ideas around statistical outreach, and the community of statistical sciences researchers continues to look to CANSSI for leadership and to engage actively with its programs. As documented in CANSSI annual reports, participants in Flagship programs win an impressive number of research distinctions as well as significant levels of external research funding for new research.

5 Access to support

CANSSI scientific programs use rigorous peer review processes to allocate resources based on applications in French or English submitted by investigators. All people involved with reviews receive training in unconscious bias. The evaluation criteria include:

The innovation and technical excellence of the proposed research, the potential for disciplinary and interdisciplinary impact, and the value-added of the proposed project.
The quality of the proposed mentoring and training program for HQP.
The qualifications of the project leads and, when relevant, of the HQP for the proposed activity.
The degree of fit with our geographic and institutional heterogeneity goals and CANSSI EDI.

The review processes vary according to program. We present a summary.

CRT	Two-part process. Supported by external reviews, the SAC evaluates LoI and invites some applicants to submit full proposals. The SAC then evaluates the full proposals. Applicants may consult with the SD and DD for support and advice during the process.
CDPF	Two-part process. In the first stage, researchers submit applications describing potential research and training for a CDPF. A subcommittee of the BOD evaluates submissions as far as meeting standards. In the second stage, HQP apply to the CDPF program, selecting specific projects of interest. The Directorate evaluates the applications of the HQP.
GSES	The applications describe the suitability of the project, the co-supervision arrangement, and the readiness of the student to undertake the experience. The Directorate evaluates based on reviews of the SD and DD. The Directorate can request external reviews.
RSG	The applications describe the suitability of the project, the application, and the partner, and the readiness of the student to undertake the experience. The Directorate evaluates based on reviews of the SD and DD. The Directorate can request external reviews.
Other	The Directorate and/or a specialized committee, e.g., CANSSI Showcase, evaluates based on short applications. External reviews can be requested.

6 Barriers to access

One barrier considered in CANSSI programs is related to the long-term goal of increasing the pool of potential users. The Florence Nightingale Day provides information about the potential for careers involving statistical sciences as well as examples of successful statistical scientists from diverse populations to high school students from underrepresented and disadvantaged populations. For undergraduate students from underrepresented and disadvantaged populations, CANSSI supports the short time scale academic approaches of datathons and summer camps. However, such approaches have limited impact, so CANSSI is also pursuing the more ambitious SURMOUNT and CRTL programs. These are aimed at directly supporting students from disadvantaged and underrepresented populations with the transition to graduate school.

Another barrier that is addressed by CANSSI arises from the fact that Canadian academic institutions are dispersed over a large geography and vary in size, mission, resources, and research activity. Moreover, there are only six statistics departments, so many statistical scientists are housed in Departments of Mathematics and Statistics as well as other departments. The local communities of statisticians are often small. This affects the statistical sciences community strongly, especially disadvantaged groups, due to issues such as lack of peer mentoring, opportunities for collaboration, connections to state-of-the-art research, institutional resources for research, and possibilities for interdisciplinary partners. The design of the CANSSI programs tackles this barrier directly.

Another barrier arose due to the early focus on the CRT program, which had the unintended consequence of limiting access to a portion of the statistical sciences community. This barrier is being reduced by the expansion to the five Flagship programs that are accessible to a much wider range of faculty and HQP. This also have the result of making CANSSI support more accessible to faculty from disadvantaged and underrepresented populations due to the barriers encountered in their academic careers, which raises challenges for reaching the position where the CRT program is accessible.

Other barriers for increasing diversity are common to all research programs, such as lack of experience with applications for external funding, minimal career mentoring, lack of support and encouragement to apply, lack of knowledge about research programs, and scarcity of examples of successful participants from diverse backgrounds. In response, CANSSI takes the following specific actions to address these challenges:

A comprehensive effort to communicate CANSSI opportunities, including emails to individuals, department representatives and chairs, advertising through the SSC and ASA networks, advertising through venues related to underrepresented and disadvantaged populations, prominent and frequent posts to the CANSSI web page and social media, frequent visits by the SD and DD to departments, and presentations by the SD and DD at conferences and townhalls. CANSSI EDI policy requires that faculty supported by CANSSI advertise available positions for HQP widely to diverse communities following requirements of their home institutions
Details about the application materials, adjudication processes, evaluation metrics are presented on the CANSSI web pages. The CANSSI adjudication committees are very diverse. The adjudication processes are followed rigorously. The application procedures allow the SD and DD to advise applicants, including commenting on draft materials and meeting in person with applicants.
CANSSI organizes multiple events, e.g., townhalls, the Showcase and the Cross-Country Tour, aimed at building community and introducing the work of young researchers. CANSSI has always put emphasis on communicating the success of faculty and students involved with its programs and is increasing this activity with the addition of a communications officer.
CANSSI-supported faculty commit to follow CANSSI EDI policies, which include working to create equitable and inclusive environments for their research teams. CANSSI staff provide EDI support.
CANSSI will build professional and EDI mentoring programs for faculty and HQP following the National Townhall in October 2021.

7 EDI Policies

Below we quote from CANSSI’s Commitment to Equity, Diversity, and Inclusion:

The creation of an equitable, diverse, and inclusive Canadian statistical sciences research enterprise is necessary for CANSSI to achieve its mission and for the statistical sciences community to respond effectively to local, national and global challenges. CANSSI actively pursues equity, diversity and inclusion through CANSSI EDI. CANSSI policies, programs, governance, and activities are evaluated on their adherence to the goal of increasing and supporting diversity by giving equitable access to opportunities, supporting equitable and inclusive participation, and creating conditions for success for all participants, which includes feeling valued and included.

CANSSI EDI includes policies that guide all aspects of CANSSI programs and activities. The relevant policies are described in all application materials and letters of award support and followed up by discussions with SD and DD. The processes for administration and selection of governance committees are stated in the Bylaws and Operating Policies. CANSSI is currently working on a comprehensive statement of EDI for CANSSI informed by the NSERC Dimensions Program, the CRC program, emerging EDI considerations across funding agencies, and university initiatives. Writing such a document is a long process as it will be reviewed and edited by the CANSSI community.

8 Consideration of underrepresented and disadvantages populations

The Florence Nightingale Day, Vancouver Datajam, Hockey Hackathon, and the future SURMOUNT program all involve significant effort in outreach and promotion to underrepresented and disadvantaged groups, as does the CANSSI Ontario International Day of Women and Girls in Science. CANSSI works with the SSC and ASA to use their outreach resources to disseminate opportunities with CANSSI to underrepresented and disadvantaged groups. CANSSI EDI policy requires leads and supervisors of CANSSI Flagship projects to use best practices for promoting opportunities in their projects to underrepresented and disadvantaged groups and to work with the resources of their home institutions to do that. The visits by the SD and DD to universities across Canada provide an opportunity to develop personal connections, with a sharp increase in the number and diversity of applications to the CRT program as one result. As part of the RSG program, SD Estep is exploring potential partnerships with disadvantaged and underrepresented communities with a need for applied research in statistical sciences.

9 Consideration of EDI in selection processes

Consideration of EDI in selection begins by evaluating the following qualities of a proposed project:

The degree to which the project satisfies the goals of broadening the community of researchers, HQP, institutions, geography, and research interests supported by CANSSI and extending the interdisciplinary reach of the statistical sciences community.
The quality of the mentoring plan for HQP including scientific and career development in addition to any program-specific EDI-related goals.
The commitment of project personnel to follow CANSSI EDI policies.

The second way that EDI is considered in selection is the evaluation criteria used for scientific programs. In addition to specific technical requirements for each program, guidelines include:

Equity across institutions and availability of local support is ensured by advising the SAC that the amount of applicant contribution to the budget of a proposed activity is not considered.
Evaluation of lead researchers focuses on qualifications directly related to the specific proposed activity and avoids criteria that favor the familiar and are biased against faculty with fewer connections, e.g., home department rank. External reviews are evaluated for unconscious bias.

The two-stage adjudication process for the CRT program reduces the effects of limited experience in applying for external funding and limited local support and mentoring. The two-stage adjudication process for CDPF widens accessibility in terms of supervisors and HQP applicants reducing some sources of implicit bias commonly found in PDF selection processes [22,23,24, 25,26,27,28,38,46].

As noted above, the diversity of research teams in Flagship programs is not as strong as the diversity among the teams leads. In response, we require projects that recruit HQP to commit to following best practices for building a diverse pool of applicants and reducing the effects of unconscious bias as determined by their home institution. At a minimum, the statement confirms that projects will:

Advertise openings in venues serving underrepresented and disadvantaged communities;
Confirm that the selection committee will consist of at least two people who have received unconscious bias training, suitable selection metrics will be determined before evaluation of candidates, and all applications will be evaluated using the same criteria.

We will monitor team composition to see if CANSSI’s policies and procedures improve the diversity.

10 Initiatives to encourage participation by under- represented and disadvantaged groups

CANSSI pursues a number of initiatives specifically designed to encourage participation in statistical sciences research, and ultimately CANSSI, by underrepresented and disadvantaged groups. Ongoing activities include support for the Vancouver Datajam, Hockey Hackathon, Data Science Bootcamp. This also includes CANSSI’s communication efforts to describe the activities and successes of researchers and HQP that take part in CANSSI programs and the visiting program to Canadian universities by the SD and DD. New initiatives include organization of the Florence Nightingale Day and the CANSSI Showcase. Finally, CANSSI is initiating elements of the SURMOUNT program.

11 Engagement activities with underrepresented and disadvantaged groups in natural sciences

The Research for Social Good (RSG)program is specifically designed to initiate collaborations between statistical scientists and organizations involved with rapidly emerging problems important to society. The RSG program is designed to support statistical scientists who are positioned to provide critical research on rapidly emerging problems important to society and to give students and PDFs the opportunity to conduct research with impacts for the good of society. The focus is on applied research that has strong potential to have a direct and immediate impact within a period of a few months. The RSG program was run for the first time in 2020 with a theme of research related to COVID-19.

The project requires a close partnership with a person or organization that has an immediate need for the research outcomes. The program supports HQP as well as the costs of data acquisition. RSG projects are initiated in two ways. CANSSI accepts applications to the program on a rolling basis. In addition, CANSSI identifies potential partnerships by approaching communities that have need for statistical research support. For example, Scientific Director (SD) Estep is pursuing opportunities through the Equity Data Commons [57] (concerning violence against women) and the Indigenous Health team at Vancouver Coastal Health [58] (concerning pandemic impacts on Indigenous peoples). The RSG program is an important component in CANSSI EDI.

By its nature, the research in CRT projects have the potential to intersect research issues relevant to underrepresented and disadvantaged groups. For example, the CRT projects Advancements to state-space models (SSMS) for fisheries science and Towards sustainable fisheries: State space assessment models for complex fisheries and biological data involved collaborations with Apoqnmatulti’k [70], which is a collaborative study that pairs Mi’kmaw and local ways of knowing with western scientific methods to track valued aquatic species in the Bay of Fundy and Bras d’Or Lake.

12 Activities that strengthen EDI awareness of organizers and participants.

CANSSI EDI includes specific actions to systematically strengthen EDI awareness through the organization of an annual program of EDI-focused activities comprising training courses, seminars, workshops, townhalls, and events revolving around EDI issues. In particular, CANSSI will work with professional organizations such as CCDI to develop an EDI training library of courses relevant to statistical sciences. CANSSI requires researchers and HQP who participate in CANSSI programs take part in a specified number of these activities. CANSSI leadership will also take the EDI training courses. Working with a consultant specializing in EDI, CANSSI will create a program to train future leaders for EDI issues in statistical sciences.

13 Dedication to EDI considerations in past and planned training activities.

Specific actions that demonstrate institutional commitment to EDI include:

Design of Flagship programs, adjudication processes, and EDI policies that encourage building diverse and inclusive research teams.
CANSSI EDI provides a dynamic and rich program of events, townhalls, and formal training courses concerned with EDI, as described above.
CANSSI has increased the research support staff to include the Program Manager, who is responsible for supporting CANSS EDI.

One challenge in ensuring HQP inclusivity in CANSSI activities is that these activities take place at universities across Canada. To tackle this problem, CANSSI imposes requirements on all projects and activities that receive CANSSI support. This includes commitment to the following:

CANSSI support will be made available to HQP in the project in an equitable way.
HQP will be supported equitably in terms of professional development and applying to participate in CANSSI programs and other opportunities for support.
Project team members and HQP will participate in the annual EDI program as specified.

Additionally, projects that anticipate recruiting HQP must follow best practices for ensuring a diverse pool of applicants and equitable selection process, as described in §II.3.4.

14 EDI consideration in the composition & selection process of governance bodies.

EDI has always been a primary consideration in the composition and selection process for the Directorate, BoD, and SAC. The goal is to ensure that the diversity of these groups reflects the diversity of statistical sciences, leads to strong scientific judgment, and demonstrates CANSSI’s commitment to EDI as the foundation for research and training activities.

15 Establishment of an equitable & inclusive research & work environment.

CANSSI takes specific actions towards EDI on two levels. Project participants supported under a CANSSI program commit to CANSSI EDI policies aimed at creating equitable and inclusive environments within research groups. This effort is sustained and supported by the EDI-focused activities and training courses organized under CANSSI EDI. CANSSI is also in the process of establishing mentoring programs for both faculty and HQP as described above. At the Institute level, during its first six years of operation, the two support staff members were part-time and worked remotely. With the establishment of the headquarters at SFU, we decided to hire staff as full-time employees of SFU, which provides them with excellent benefits, employment protection, and human resource support. SFU provides training in creating equitable and inclusive working environments that is taken by all team members. We use a team-based approach to manage CANSSI operations and activities that values the contributions of each team member and reinforces fallback support.

16 Measurable and relevant objectives

Measurable and Relevant Objectives

Increase usage of CANSSI programs, increase number of new collaborations in statistical sciences, increase numbers of unique leads and supervisors in Flagship projects, improve balance in career stage of faculty involved with CANSSI programs, increase diversity in applications to CANSSI programs

Present an updated comprehensive CANSSI EDI document at the 2022 annual general meeting.

Establish national mentoring programs for faculty.

Establish CANSSI EDI activities focused on outreach and overcoming barriers for underrepresented and disadvantaged groups.

Establish rigorous process for evaluating the efficiency, impact, and effectiveness of CANSSI EDI. Conduct thorough reviews of the impact of CANSSI support on the careers of individual researchers, on any potential biases in CANSSI adjudication processes and metrics, and on the impact and effectiveness of CANSSI EDI policies for supported projects.

Establish partnerships and collaborations with underrepresented and disadvantaged communities and organizations representing underrepresented and disadvantaged groups in natural sciences and engineering that have a need for statistical sciences research.

Build awareness and knowledge of EDI issues in the Canadian statistical sciences community by widespread, repeated participation in EDI training courses organized by CANSSI. Develop a program to train faculty in EDI leadership.

Evaluate the effectiveness of CANSSI EDI policies for creating inclusive and equitable research conditions for HQP in projects supported by CANSSI.

Establish CRTL and initiate elements of SURMOUNT.

References

	The Future of Data Analysis, J. Tukey. Annals of Mathematical Statistics 33, 1962, 1-67.
	Modern Interdisciplinary University Statistics Education, Committee on Applied and Theoretical Statistics, Board on Mathematical Sciences, Commission on Physical Sciences, Mathematics, and Applications, National Research Council. Washington D.C., 1994.
	Facilitating Interdisciplinary Research, Committee on Facilitating Interdisciplinary Research and Committee on Science, Engineering, and Public Policy, National Academies. Washington D.C., 1994.
	Groups of Diverse Problem Solvers Can Outperform Groups of High-Ability Problem Solvers, L Hong, S.E. Page. Proceedings of the National Academy of Sciences 101, 2004, 1638-1639.
	Applied Mathematics at the Department of Energy: Past, Present, and a View to the Future, D. Brown, J. Bell, D. Estep, W. Gropp, B. Hendrickson, S. Keller-McNulty, D. Keyes, J. Tinsley Oden, L. Petzold, M Wright. U.S. Department of Energy, 2008. A report by an independent panel from the applied mathematics research community.
	National Institute for Complex Data Structures (NICDS). A national institute whose mandate was to enrich and enlarge the national research enterprise through a powerful new model for the statistical sciences. The NICDS fostered nationally coordinated projects with statistical leadership and a substantial interaction with researchers in science and health. Projects advanced research frontiers in other disciplines through the development of novel methods for large-scale problems involving complex data sets. The NICDS received its primary support from NSERC during 2003-2008.
	The Impact on Mentoring During Postgraduate Training on Doctors’ Career Success, M. Stamm and B. Buddeberg-Fischer. Medical Education 45, 2011, 488-496.
	What Makes a Team Smarter? More Women, A. Woolley, T. Malone, A. Bernato. Harvard Business Review 89, 2011, 32-33.
	Improving Graduate Education to Support a Branching Career Pipeline: Recommendations Based on a Survey of Doctoral Students in the Basic Biomedical Sciences, C. Fuhrmann, D. Halme, P. O’Sullivan, and B. Lindstaedt. CBE – Life Sciences Education 10, 2011, 239-249.
	Science PhD Career Preferences: Levels, Changes, and Advisor Encouragement, H. Sauermann and M Roach. PLOS ONE 7, 2012.
	How Diversity Can Drive Innovation, S. Hewlett, M. Marshall, L. Sherbin. Harvard Business Review, 2013.
	Solutions for a Complex Age. Long Range Plan for Mathematical and Statistical Sciences Research in Canada 2013-2018, Long Range Plan Steering Committee for the Mathematical and Statistical Sciences. NSERC, 2013.
	Collaborative and Thematic Resources Support in Mathematics and Statistics Program (CTRMS) NSERC. The objective of the CTRMS Program was to enable the development of research activities and foster training and collaboration, within and among national or international (based in Canada) thematic research resources in mathematical and statistical sciences.
,	Gender Diversity with R&D Teams: Its Impact on Radicalness of Innovation, C. Diaz-Garcia, A. Gonzalez-Moreno, F.J. Saez-Martinez. Innovation: Management, Policy, & Practice 15, 2013, 149-160.
	Strength in Numbers: The Rising of Academic Statistics Departments in the U.S., A. Agresti, X-L Meng, Editors. Springer, New York, 2013.
	Statistics in Action: A Canadian Outlook, J. Lawless Editor. CRC Press, Boca Raton, Florida, 2014.
	Discovery with Data: Leveraging Statistics with Computer Science to Transform Science and Society. American Statistical Association, 2014.
	Women Flocking to Statistics, the Newly Hot High-Tech Field of Data Science, B Schulte. Washington Post, 12/19/2014.
	Biomedical Science Ph.D. Career Interest Patterns by Race/Ethnicity and Gender, K. Gibbs Jr., J. McGready, J. Bennett, and K. Griffin. PLOS ONE 9, 2014.
	The Role of Statistics in Data Science – An ASA Statement, R. Wasserstein. American Statistical Association, 2015.
	Interdisciplinary Research by the Numbers, R. Noorden. Nature 525, 2015.
	Expectations of Brilliance Underlie Gender Distributions Across Academic Disciplines, S.J. Leslie, A. Cimpian, M. Meyer, E. Freeland. Science 347, 2015, 262-265.
	Limits to Meritocracy? Gender in Academic Recruitment and Promotion Processes, M. Nielsen. Science and Public Policy 43, 2015.
	Systematic Inequality and Hierarchy in Faculty Hiring Networks, A. Clauset, S. Arbesman, and D. Larremore. Sciences Advances 1, 2015,
	Causes and Consequences of Inequality in the STEM: Diversity and Its Discontents, S. Alegria and E. Branch. International J. Gender, Science, and Technology 7, 2015, 321-342.
	Which Gender Gap? Factors Affecting Researchers’ Scientific Impact in Science and Medicine, C. Beaudry, V. Lariviére. Research Policy 45, 2016, 1-28.
	From the NIH: A Systems Approach to Increasing the Diversity of the Biomedical Research Workforce, H. Valantine, P. Lund, and A. Gammie. CBE Life Sciences Education 15, 2016.
	Gender, Race/Ethnicity, and National Institutes of Health R01 Research Awards: Is There Evidence of a Double Bind for Women of Color?, D. Ginther, S. Kahn, and W. Schaffer. Academic Medicine 91, 2016, 1098-1107.
	50 Years of Data Science, D. Donoho. J. Computational and Graphical Statistics 26, 2017, 745-766.
	The Equity Myth: Racialization and Indigeneity at Canadian Universities, F. Henry, E. Dua, C. James, A. Kobayashi, P. Li, H. Ramos, M. Smith. UBC Press, Vancouver, 2017.
	Big Data Hub, Simon Fraser University. The BDH connects industry and communities with SFU partners and experts to address challenges and opportunities around data to grow a competitive economy and deliver social impact. Established in 2017.
	Degrees of Difference: Gender Segregation of U.S. Doctorates by Field and Program Prestige, K. Weeden, S. Thébaud, D. Gelbgiser. Sociological Science 4, 2017.
	How Diversity Matters in the US Science and Engineering Workforce: A Critical Review Considering Integration in Teams, Fields, and Organizational Contexts, L. Smith-Doerr, S. Alegria, and T. Sacco. Engaging Science and Technology 3, 2017, 139-153.
	Overview of Statistics as a Scientific Discipline and Practical Implications for the Evaluation of Faculty Excellence, C. Goad, N. Keuler, M. Kramer, J. Lee-Bartlett, B. Momen, J. Osborne, N. Paton, A. Rendahl, J. Sharp, J. Stevens, R. Tempelman, B. Yandell, K. Yeater. American Statistical Association, 2018.A position paper of the American Statistical Association.
	Statistical Science in the World of Big Data, N. Reid. Statistics and Probability Letters 136, 2018, 42-45.
	The Status of Statistics Education in Canada, S. Damouras and S. Kang. Liaison Newsletter 32, 2018.
	Sexual Harassment of Women: Climate, Culture, and Consequences in Academic Sciences, Engineering and Medicine, P. Johnson, S. Widnall, and F. Benya, Editors. National Academies of Sciences, Engineering, and Medicine, The National Academies Press, Washington D.C., 2018.
	Special Issue on Collaborative Research Team projects of the Canadian Statistical Sciences Institute. Canadian J. Statistics 47, 2019.
	Artificial Intelligence – The Revolution hasn’t Happened Yet, M. Jordan. Harvard Data Science Review 1, 2019.
	Statistics at the Crossroads: Who is for the Challenge? J. Berger, X. He, D. Madigan, B. Yu, J. Wellner, et al. National Science Foundation, 2019.
	Data Science: An Artificial Ecosystem, X-L Meng. Harvard Data Science Review 1, 2019.
	Equity, Diversity and Inclusion: Glossary of Terms, Equity, Diversity and Inclusion (EDI) Committee, Department of Epidemiology, School of Public Health. University of Washington, 2019.
	(Bio)Statistics Bachelor’s Degrees Nearly Quintuple This Decade. Amstatnews, American Statistical Association, 2019. Highlights from the 2018 Degree Release.
	Topic Choice Contributes to the Lower Rate of NIH Awards in African-American/Black Scientists, T. Hoppe, A. Litovitz, K. Willis, R. Meseroll, M. Perkins, and B. Hutchins, A. Davis, M. Lauer, H. Valantine, J. Anderson and G. Santangelo. Science Advances 5, 2019, 1-12.
	Statistics Canada Postsecondary Student Information System. Private communication from S. Damouras, 2019.
	Best Practices in Equity, Diversity and Inclusion in Research. NSERC, 2020. A guide for applicants to New Frontiers in Research Funds competitions.
	Challenges and Opportunities in Statistics and Data Science: Ten Research Areas, X. He and X. Lin. Harvard Data Science Review 2, 2020.
	What is Interdisciplinary Research. National Science Foundation, 2020.
	Consequences of the COVID-19 Pandemic on Manuscript Submissions by Women, M. Kibbe. Jama Surgery 155, 2020.
	Unequal Effects of the COVID-19 Pandemic on Scientists, K. Myers, W. Tham, Y. Yin, N. Cohodes, J. Thursby, M. Thursby, P. Schiffer, J. Walsh, K. Lakhani and D. Wang. Nature Human Behavior 4, 2020, 880-883.
	Why We Publish Where We Do: Faculty Publishing Values and Their Relationship to Review, Promotion and Tenure Expectations, M. Niles, L. Schimanski, E. McKiernan, and J. Alperin. PLOS ONE 15, 2020.
	A Decade of Decline: Grant Funding for Researchers with Disabilities 2008 to 2018, B. Swenor, B. Munoz, and L. Meeks. PLOS ONE 15, 2020.
	Publish or Perish: Women in Research Call for an End to Systemic Discrimination, C. Larochelle, et al. University Affairs, 2020.
	CANSSI Research Training Library (CRTL), CANSSI Strategic Retreat Report, 2020. The goal of CRTL isto provide students at all Canadian universities and colleges access to advanced preparation for research by housing materials for graduate research-level courses. It is motivated by the fact that students at some resource-constrained universities have limited access to research-level coursework and this affects their preparation for future careers and their competitiveness in seeking employment. The pressures of exploding enrollments means that many departments have need for the program. A CRTL course package includes recorded lectures, lecture notes, assignments and assessments, projects, data sets, and auxiliary materials. The packages can be used in a variety of ways, e.g., as a basis for a reading course (organized locally) or for use by a faculty member teaching a course for the first time. Packages are offered in English and French. As a preliminary entry, CANSSI is supporting the development of a module-based course on communications, ethics, interdisciplinary research that will be made available to all graduate programs in Canada. The selection of course packs and developers are guided by the Statistical Education Section of the SSC supported by an adjudication process that CANSSI organizes. There are calls to extend CRTL to include advanced elective materials for undergraduate degrees to deal with inequities in preparation for graduate studies. The plan is to develop a partnership between government, university and industry to support the program.
	Discovery Grants Program (DPG). The Discovery Grants program supports ongoing programs of research of individual researchers with long-term goals rather than a single short-term project or collection of projects.
	Natural Sciences and Engineering Research Council of Canada (NSERC) supports fundamental research in the natural sciences and engineering. It is one member of the Tri-Council Canada. The other two members are the Canadian Institutes of Health Research (CIHR) and the Social Sciences and Humanities Research Council (SSHRC). Operated by the Canadian government, the Tri-Council supports and promotes high-quality research in a wide variety of disciplines and areas.
	Equity Data Commons, Simon Fraser University. EDC is designed to create a national community-academic partnership hub to provide access to resources, expertise and infrastructure for data. The goal is to ensure that communities have access to the latest innovations in data analytics, statistical analysis, research ethics, big data, artificial intelligence, visualization and advanced computation.
	Vancouver Coastal Health. Vancouver Coastal Health provides health-care services through a network of hospitals, primary care clinics, community health centres and long-term care homes.
	NSERC views diversity in terms of a range of intersecting identity factors including race, colour, place of origin, religion, immigrant and newcomer status, ethnic origin, ability, sex, sexual orientation, gender identity, gender expression, and age. NSERC is committed to reducing obstacles faced by but not limited to women, Indigenous Peoples, persons with disabilities, members of visible minority or racialized groups, and members of LGBTQ2+ communities. Dimensions, Tri-Agency, 2021.
	New Frontiers in Research Fund (NFRF) is operated under Canada’s Tri-Agency Institutional Programs Secretariat. It was launched in late 2018 to support world-leading interdisciplinary, international, high-risk/high-reward, transformative and rapid-response Canadian research. The fund has a budget of $275 million over five years (2018–19 to 2022–23) and will grow to have an annual budget of $124 million in 2023–24.
C	Canadian Centre for Diversity and Inclusion (CCDI), An institution that assists organizations to increase inclusivity and decrease prejudice and discrimination and to generate the awareness, dialogue and action for people to recognize diversity as an asset and not an obstacle.
	SURMOUNT, D. Estep, 2021. SURMOUNT takes inspiration from US National Science Foundation Research Experiences for Undergraduates and Integrative Graduate Education and Research Traineeship programs and collaborations between US universities and minority-serving institutions such as MTBI [69]. SURMOUNT tackles barriers spanning socio-economic conditions to educational inequities that challenge students from underrepresented and disadvantaged populations with the potential to undertake graduate studies. The key approach is to bring students to a research-intensive host university at the beginning of the summer after the third year of studies and then to complete their fourth year at the host university. During this period, the students will engage in an innovative curriculum, sculpted research experiences, social and mentoring programs designed to help the students navigate graduate school. The students will remain engaged with their home institutions, especially with their advisors and communities, and ultimately earn their degree from their home institutions. There are two components to SURMOUNT. The initial phase of the summer program after the third year offers a sustained introduction to research working with groups of faculty, graduate students, PDFs and peers in a supportive environment that creates an equitable and inclusive foundation for participation. During the subsequent academic year, students will remain engaged with undergraduate research, take advanced coursework, and undertake specialized mentoring and advising. Throughout, the students will be supported financially. SURMOUNT requires a partnership between educational institutions, research institutes, government agencies and industry. CANSSI has a key role in the program and will undertake aspects of SURMOUNT, e.g., the summer component, as a first step for building the partnerships needed to operate the full program.
	Data Science for Social Good, it is an interdisciplinary and applied research training program that partners with public organizations to extract insights from open and proprietary data sets. Operated by University of British Columbia.
	Statistics Canada is the national statistical office. The agency ensures Canadians have the key information on Canada’s economy, society and environment that they require to function effectively as citizens and decision makers.
	UNESCO International Geoscience Programme (IGCP) serves as a knowledge hub of UNESCO to facilitate international scientific cooperation in the geosciences. The IGCP mission includes promoting sustainable use of natural resources, advancing new initiatives related to geo-diversity and geo-heritage and geohazards risk mitigation. The IGCP promotes collaborative projects with a special emphasis on the benefit to society, capacity-building, and the advancement and sharing of knowledge between scientists with an emphasis on North-South and South-South cooperation.
	Digital Technology Supercluster. Mobilizes industry-led collaboration and co-investment across the health, natural resources and industrial sectors. Canadian technology companies, academia, researchers and public stakeholders work together to grow digitally skilled talent and tackle real-world problems related to well-being, climate change and digital enterprise transformation.
	National Research Council (NRC) is Canada’s largest federal research and development organization.
	Mathematical and Theoretical Biology Institute (MTBI), now called Quantitative Research for the Life and Social Sciences Program, Arizona State University
	The Statistical and Applied Mathematical Sciences Institute, 2002-2021. SAMSI is a National Science Foundation Mathematical Sciences Institute operated as a partnership of Duke University, North Carolina State University, and the University of North Carolina (Chapel Hill).
	Apoqnmatulti’K. Apoqnmatulti’k pairs Mi’kmaw and local ways of knowing with western scientific methods to learn more about the movements and habitat use of katew (American eel), jakej (American lobster) and punamu (Atlantic tomcod) in parts of Mi’kma’ki (the ancestral and unceded territory of the Mi’kmaq in what is now Atlantic Canada). Project leaders, who include Mi’kmaw knowledge holders, commercial fishers, academic researchers, and government scientists are working together to conduct acoustic telemetry studies that will link animal movement to environmental factors.
	Science Alive, Faculty of Applied Sciences, SFU. funded by the NSERC PromoScience program, Science Alive strives to engage youth in hands-on Science, Technology, Engineering, Art & design, Mathematics programs to build measurable skills and improve self-confidence.

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