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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/gender-analytics-inclusive-analytics
课程评论：没有评论
课程名称：包容性分析技术 课程概述：许多我们认为是性别中立的政策、产品、服务或流程，实际上会产生性别化的结果。从除雪到汽车安全，从投资顾问到基础设施投资，这些影响在性别上会有不同的效果。如果再考虑种族、土著身份、能力差异、民族、性取向等身份交叉因素，这些结果可能会更加偏颇。那么，我们应该如何改变这一现状？如何避免偏见风险或利用基于性别的见解创造创新的新产品？ 《包容性分析技术》将为您提供揭示这些交叉见解的工具和分析技术。课程涵盖定量和定性数据的收集与分析，包括基本统计技术，以及与客户、受益人及其他利益相关者合作的实用指导。您将学习如何结合来自多个来源的丰富证据，从而发展出如何使政策、产品、服务和流程更公平、或更好服务于独特社区的创新见解。 该课程是多伦多大学罗特曼管理学院性别分析专业的第二门课程。单独学习此课程很有价值，如果作为整个专业的一部分学习，则能获得更多收获。 课程大纲： 第一部分：包容性数据收集中的伦理和法律考虑 描述：了解在不同社区收集和分析数据时，如何处理这些行为对边缘化个体和群体所带来的脆弱性。学习与数据收集、存储、分析和传播相关的法律及伦理框架。 第二部分：从性别视角进行定量数据分析：概率 描述：复习定量数据分析的基本原则，包括概率和假设检验。最终能够进行基本的定量数据分析计算并理解统计推断。 第三部分：从性别视角进行定量数据分析：数据与解读 描述：揭示数据的生成过程，以及如何从数据中提取性别化见解。学习在哪里找到性别分解的数据，分析关系并解读结果。 第四部分：定性数据收集：与利益相关者的社区参与 描述：应用性别视角分析数据的重要部分是获取不同的观点，尤其是来自弱势群体的视角。学习如何进行有意义的社区参与，并了解如何负责任地与脆弱或边缘化的社区接触。
Part: 1
Title:Ethical and legal considerations in inclusive data collection
Description: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.
Part: 2
Title:Quantitative data analysis through a gender lens: probability
Description: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.
Part: 3
Title:Quantitative data analysis through a gender lens: data and interpretation
Description: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.
Part: 4
Title:Qualitative data collection: community-based engagement with stakeholders
Description: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.
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? Inclusive Analytics Techniques will provide you with the tools and analytical techniques to uncover these intersectional insights. The course covers both quantitative and qualitative data collection and analysis, including basic statistical techniques and practical instructions for working with customers, beneficiaries and other stakeholders. You will learn to incorporate multiple sources of rich evidence in order to develop innovative insights into how policies, products, services and processes can be made more equitable or serve unique communities. This is the second course of the Gender Analytics Specialization offered by the Institute for Gender and the Economy (GATE) at the University of Toronto's Rotman School of Management. It's great on its own, and you will get even more out of it if you take it as part of the Specialization.
