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Policies Through Gender Inclusive Data Analytics

Empowering Policies through Gender-Inclusive Data Analytics

Session Report

The Generation Alpha Data Centre, at IMPRI Impact and Policy Research Institute, New Delhi conducted a Four-Day Immersive Online Certificate Training Course on ‘Data Analytics for Policy Research’ from November 4th to 25th, 2023. 

The course, spread over four-consecutive days, helped to equip policymakers, researchers, and data enthusiasts with cutting-edge analytical skills. In this course, we went beyond theory and provided hands-on training in data analytics techniques, empowering participants to derive meaningful insights from complex datasets

On the third day our third speaker, Dr Vibhuti Patel, Visiting Distinguished Professor, IMPRI; Vice-President, Indian Association of Women Studies; Former Professor of Economics, Tata Institute of Social Sciences (TISS), Mumbai opened the conversation by setting the tone for a comprehensive exploration of the significance of accurate statistics in addressing gender-based differences and inequalities across various facets of life. Dr. Patel’s precise and factual opening creates a foundation for an insightful session on the nuances of data analytics for informed policy decision-making.

Introduction to Gender Mainstreaming in Monitoring and Evaluation

Dr. Patel initiates the session by emphasizing the importance of accurate statistics that adequately reflect differences and inequalities in the situations of men, women, and the gender spectrum across various aspects of life. She contends that having precise statistics is vital for effectively addressing problems.

Historical Context: Beijing Platform (1995)

She delves into the historical context, citing the Beijing Platform in 1995, where representatives from over 200 countries adopted recommendations emphasizing the collection, compilation, analysis, and presentation of statistics by sex and age. This, she explains, laid the foundation for gender mainstreaming.

Challenges in Data Collection: Gender Stereotypes

Dr. Patel points out the challenges in data collection, particularly regarding gender stereotypes. She illustrates how stereotypes lead to underreporting and misclassification of women’s economic activities, citing examples from the workforce, agriculture, and other sectors.

Unpaid Care Work and Gender Bias in Data Collection

The discussion extends to the issue of unpaid care work, where Dr. Patel highlights how the current data collection methods often overlook or undervalue the contributions made by women in household and caregiving activities. This bias, she argues, affects policy interventions and perpetuates inequalities.

Impact of Gender Stereotypes on Policy Interventions

The impact of gender stereotypes on policy interventions becomes evident as Dr. Patel discusses the representation and recognition of women-headed households. Despite being among the poorest, these households often go unnoticed in development and welfare schemes due to statistical biases.

Intersectionality and Diversity in Data Collection

Dr. Patel emphasizes the need for intersectional data collection, considering diverse characteristics such as disability, age, and gender. She illustrates this with examples from countries like Vietnam, where disability statistics played a crucial role in economic planning post-conflict.

Concepts and Definitions in Data Collection

The speaker underscores the importance of concepts and definitions in data collection, arguing that the criteria for defining the workforce should be inclusive of various economic activities, especially unpaid work done by women.

Gender Statistics for Decision-making

The session underscores the role of gender statistics in decision-making processes. Dr. Patel argues that accurate data is essential for governments to address gender-based violence, health outcomes, education, and representation in decision-making bodies.

Conclusion: Towards Effective Gender Mainstreaming

In conclusion, Dr. Vibhuti Patel advocates for a comprehensive gender mainstreaming strategy that begins with assessing and addressing the root causes of gender differences. She emphasizes the role of accurate and inclusive gender statistics in guiding effective policy research and development.

Dr. Patel’s insightful session provides a holistic perspective on the challenges and opportunities in utilizing data analytics for gender mainstreaming in policy research. Participants are left with a deeper understanding of the nuances involved and the imperative for accurate and inclusive data in shaping policies that cater to diverse gender needs.

Disclaimer: All views expressed in the article belong solely to the author and not necessarily to the organisation.

Acknowledgment: Rahul Soni is a research Intern at IMPRI.

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