Many policies, products, services or processes that we think of as gender-neutral actually have gendered outcomes. Everything from snow plowing to car safety to investment advising to infrastructure investment has impacts that differ by gender. These outcomes can be even more biased if we look at important intersections with race, indigeneity, differences in ability, ethnicity, sexual orientation, and other identities. The question is, what can you do to change this? And, how can you avoid the risks of bias or create innovative new offerings using gender-based insights?
Этот курс входит в специализацию ''Специализация Gender Analytics: Gender Equity through Inclusive Design'
от партнера
Специализация Gender Analytics: Gender Equity through Inclusive DesignТоронтский университетОб этом курсе
Недавно просмотрено: 4 439
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100% онлайн
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Курс 2 из 5 в программе
Прибл. 8 часов на выполнение
Английский
Субтитры: Английский
Чему вы научитесь
Understand legal & ethical frameworks for collecting, storing, analyzing, and disseminating data to reduce vulnerabilities for marginalized people.
Examine how quantitative data is produced, identify gender-related data gaps; & use analytics skills to uncover intersectional gender-based insights
Collaborate with stakeholders to gain an in-depth understanding of unmet needs using community-based and ethnographic research methods
Learn quantitative & qualitative research and analysis techniques; explore how to integrate insights from both types of data to generate insight.
Приобретаемые навыки
Business AnalyticsGender Based AnalysisQualitative and Quantitative Data AnalysisStakeholder Analysiscommunity engagement
Гибкие сроки
Назначьте сроки сдачи в соответствии со своим графиком.
Сертификат, ссылками на который можно делиться с другими людьми
Получите сертификат по завершении
100% онлайн
Начните сейчас и учитесь по собственному графику.
Курс 2 из 5 в программе
Прибл. 8 часов на выполнение
Английский
Субтитры: Английский
от партнера
Торонтский университет
Established in 1827, the University of Toronto is one of the world’s leading universities, renowned for its excellence in teaching, research, innovation and entrepreneurship, as well as its impact on economic prosperity and social well-being around the globe.
Программа курса: что вы изучите
2 ч. на завершение
Ethical and legal considerations in inclusive data collection
When collecting and analyzing data from diverse communities, it is important to recognize that this can create vulnerabilities for marginalized individuals and groups. In this module, you will learn about the legal frameworks and ethical requirements related to collecting, storing, analyzing, and disseminating data, paying attention to different country contexts. By the end of the week, you will understand potential risks to research participants and find ways to mitigate such risks and appropriately compensate them for their time and efforts in the data collection and design process. These considerations are important to take into account before you move forward with any data collection and analysis projects.
2 ч. на завершение
6 видео ((всего 22 мин.)), 4 материалов для самостоятельного изучения, 1 тест
2 ч. на завершение
Quantitative data analysis through a gender lens: probability
This session will review basic principles of quantitative data analysis, including probability and hypothesis testing, through fun examples and exercises. By the end of the week, you will be able to conduct basic calculations to analyze quantitative data and develop the intuition behind statistical inference and hypothesis testing to understand analytical reports generated by others.
2 ч. на завершение
8 видео ((всего 62 мин.)), 3 материалов для самостоятельного изучения, 1 тест
2 ч. на завершение
Quantitative data analysis through a gender lens: data and interpretation
This week, we will shed light on how data is produced and how to uncover gender-based insights from data. By the end of the week, you will understand the data generation process, know where to locate sources of gender-disaggregated data, and analyze relationships to interpret results. You will see how emerging insights from gender-disaggregated data analysis can shape the evolution of the problem statement and identify areas for further data collection.
2 ч. на завершение
7 видео ((всего 50 мин.))
2 ч. на завершение
Qualitative data collection: community-based engagement with stakeholders
A big part of applying a gender lens to data analysis is obtaining different perspectives, especially from underrepresented groups. One way to do this is through qualitative research in the communities of interest. This week, you will explore the art of meaningful community engagement. By the end of this week, you will have a better understanding of the concept and value of community engagement as a qualitative data source. You will learn the steps to collect and analyze qualitative data to gain insight into people’s emotions, motivations, aspirations, and pain points. You will also learn how engage responsibly with vulnerable or marginalized communities.
2 ч. на завершение
12 видео ((всего 62 мин.)), 3 материалов для самостоятельного изучения, 1 тест
Рецензии
Лучшие отзывы о курсе INCLUSIVE ANALYTIC TECHNIQUES
от партнера TM28 дек. 2020 г.
I have a fear of maths, but this course and the professor were extremely engaging and it was a lot of fun to study and come out of this course with great insights
от партнера KA15 апр. 2021 г.
Great course with diverse instructors that delivered a lot of material in a concise and accessible manner!
Специализация Gender Analytics: Gender Equity through Inclusive Design: общие сведения
Current conversations about diversity & inclusion often forget that these are not just HR issues but affect how products, services, processes & policies create outcomes that differ by gender, race, differences in ability, indigeneity & other intersecting identities. Gender Analytics is a methodology that allows you to create opportunities for business or policy impact by using gender-based insights to design transformational solutions. More here...
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