Training Program in Detail

Main navigation

The 2023-24 CAnD3 Annual Report is here!

On this page: CAnD3 Training Program Syllabus Training Program Objectives Skills Training Areas Substantive Training Areas Training Timetable Fostering Exchange Experiential Learning Expected Outcomes

听

CAnD3 Training Program Syllabus

CAnD3鈥檚 primary goal is to collaboratively develop, implement, and deliver an innovative training program 鈥� Population Analytics in an Aging Society 鈥� to equip the next generation of academic and applied population researchers with the knowledge, skills, and networks to support data-driven decision-making in aging societies. From its inception in 2020, CAnD3 has delivered our annual, international fellowship program anchored in interdisciplinary and intersectoral exchange to graduate students and post-doctoral researchers.

View the syllabus

Training Program Objectives

Across the duration of the 12-month training program, participants will:

Acquire knowledge in population aging听from multiple disciplinary perspectives in relation to four axes.
Build basic skills in population data science and computational population social science.
Gain an understanding of the data-to-decision-making processes in non-academic sectors.
Build pan-Canadian, multidisciplinary, intersectoral, and international professional networks.
Develop professional skills, such as group discussion and meeting facilitation (online and in-person).
Apply knowledge, analysis, and skills to investigating real-world听research questions and communicating results.

Skills Training Areas*

Population Aging Research Modules

Population research using linked administrative data (Module partner: Statistics Canada)

Research replicability and workflow management (Module partner: Canadian Research Data Centres Network)

Inclusion, Diversity, Equity and Accessibility (IDEA) (Module partner: Women and Gender Equality Canada; Statistics Canada)

Population Data Science & Computation Population Research Modules

Social media and demographic methods (Module partner: University of Toronto)

Population data visualisation (Module partners: Population Data BC &听Geographic Information Centre, 海角社区)

Machine learning for social scientists (Module partner: Quantitative Methods in the Social Sciences, ISERP, Columbia University)

Data-Driven Decision-Making Modules

Population data visualization for decision-making audiences听(Module partner: Statistics Canada & Health Canada)

Evidence-informed decision-making and policy (Module partner: (Policy Community Partnership Office)

Knowledge mobilization to maximize research impact (Module partner: Statistics Canada and others)

Plain language writing for data-driven decision-making

听

Substantive Training Areas*: Population Aging Through Four Axes

Lectures and learning materials will be provided by consortium members and their colleagues from multiple disciplines, universities, and countries. See our events page for current and previous CAnD3 Lunch&Learn lectures.听

Family and Social Inclusion听

This axis examines how families have changed over time, and how these changes affect family member鈥檚 health, wealth, and happiness.

Education, Labour, and Inequality

This axis examines how critical institutions of education and work shape our lives, and their interplay with one of the most critical policy challenges of the past decades, namely the secular rise in inequality.

Migration and Ethnicity听

This axis examines how migration, ethnicity and indigenous issues are interwoven in the increasing pace of globalisation that we have witnessed in the 21^st century.

Well-Being and Autonomy听

This axis examines how social and economic factors, as well as institutions and policies, shape individuals鈥� vulnerability to and experience of well-being and autonomy.

*Because the CAnD3 training program is co-constructed by its members and partners, responding to changing partner needs, the specific modules in each skills and substantive area are subject to change.

Training Timetable

The exact order and title of topics are currently in progress and may be subject to change. See CAnD3 2021-22 calendar

听	September - June	Jul - Aug	Total
Substantive	Monthly modules, including lectures, readings, and group discussions; Both consortium-wide and trainee-only learning activities听	Not applicable	60 hours
Skills-Based	Monthly modules of hands-on skills training & assignments; Both consortium-wide and trainee-only learning activities	Not applicable	70 hours
Peer-to-Peer	Bi-weekly group learning activities and support听	Not applicable	20 hours
ePortfolio	Reflective learning through ePortfolio		20 hours
Experiential	Applied research project (variable duration) OR		160+ hours
Experiential	Optional paid internship		160+ hours
Trainees can expect to spend min average of 5 hours/week on training plus an applied research project or internship

Fostering Exchange

The Population Analytics in an Aging Society Training program fosters international, multidisciplinary, and intersectoral exchange through:

Experiential Learning听

CAnD3 experiential learning includes:

In keeping with the co-construction model of CAnD3, our partners will provide problems, research questions, data, context, scope, links to decision-making, and key deliverable requirements for internship and applied research projects. Academic, government, not-for-profit, and private partners will be active in supervising and mentoring trainees for internships and applied research projects.

Expected Outcomes听

Training Outcomes

Equip the next generation of population researchers to collaborate with academic, public, private and not-for-profit sectors.

Facilitate trainees鈥� transition into the workforce, whether in or out of academia

Through continuous learning and improvement, produce and widely share knowledge, lessons learned and best practices on extra-curricular graduate training in population analytics.

Academic Outcomes

Build enduring linkages across disciplines, sectors, and countries that will strengthen the multidisciplinary population research community and expand our understanding of population aging and its implications across the social sciences.

Expand the capacity of population social scientists to participate fully, offer empirical insights, and communicate effectively in these important discussions and debates in both academic and public spheres.