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Bewertung und Feedback des Lernenden für Gender Analytics for Innovation von University of Toronto

198 Bewertungen

Über den Kurs

Gender Analytics is a way to analyze your products, services, processes and policies with a gender lens to uncover hidden opportunities for innovation and effectiveness. We'll answer questions such as: Why are women 47% more likely than men to be injured when they get in a car accident? Why do financial products fail to meet women’s needs across their life cycles? Why will automation and AI be more likely to impact women than men? Why are gender-neutral policies are not necessarily gender-equal? This is the introductory course in the 5-course Gender Analytics Specialization offered by the Institute for Gender and the Economy (GATE) at the University of Toronto's Rotman School of Management. In this course, you will build the foundations for conducting Gender Analytics. You will get comfortable with the concepts and terms associated with Gender Analytics, including sex, gender, gender identity, sexual orientation and intersectionality. You will examine how policies, products, services and processes may have unintentionally gendered outcomes that miss out on opportunities or create needless risks. You will learn to uncover assumptions underlying these policies, products, services and processes, and to break social, cultural, and or organizational norms that perpetuate exclusion and inequality. You will see how Gender Analytics can lead to transformational innovations. You will also evaluate your own competencies and start your Self Development Plan and begin your journey to build a workplan for your own Gender Analytics project....



26. Feb. 2021

I have learned so much on this first module of the Gender specialization program seeing it from different angles and especially on how to promote diversity and inclusivity.


13. Dez. 2020

I hadn't intended to finish the course so soon. I still planned to go back and do the assessments over again to raise my mark. Not sure if I can still do that or not.

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