Podcast
Questions and Answers
Which of these is NOT considered a key principle of data feminism?
Which of these is NOT considered a key principle of data feminism?
- Rethink Binaries and Hierarchies
- Understand the history of technology (correct)
- Embrace Pluralism
- Challenge Power
How does data feminism challenge the dominant narratives in data science?
How does data feminism challenge the dominant narratives in data science?
- By focusing solely on the experiences of women.
- By promoting the use of data in a way that reinforces existing power structures.
- By ignoring the role of technology in social change.
- By centering marginalized perspectives and offering alternative approaches to data analysis. (correct)
What is the significance of "embracing pluralism" in the context of data feminism?
What is the significance of "embracing pluralism" in the context of data feminism?
- It encourages using standardized data collection methods for all groups regardless of their cultural contexts.
- It encourages ignoring the complexities of human experiences and focusing on a single, universal truth.
- It emphasizes the importance of recognizing and valuing diverse perspectives and knowledge systems. (correct)
- It advocates for prioritizing quantitative data over qualitative data.
What is the intended outcome of examining power in the context of data feminism?
What is the intended outcome of examining power in the context of data feminism?
What does the text suggest about the application of data feminism in practice?
What does the text suggest about the application of data feminism in practice?
Which of the following best illustrates the concept of "Challenge Power" within the framework of data feminism?
Which of the following best illustrates the concept of "Challenge Power" within the framework of data feminism?
Which of the following scenarios best demonstrates the application of "Embrace Pluralism" in data feminism?
Which of the following scenarios best demonstrates the application of "Embrace Pluralism" in data feminism?
Which of the following statements best aligns with the core idea of "Examine Power" as it relates to data feminism?
Which of the following statements best aligns with the core idea of "Examine Power" as it relates to data feminism?
Which of the following exemplifies the unique approach of data feminism in addressing societal issues?
Which of the following exemplifies the unique approach of data feminism in addressing societal issues?
Data feminism emphasizes examining how power is distributed in society. What is the primary goal of this examination?
Data feminism emphasizes examining how power is distributed in society. What is the primary goal of this examination?
What does the principle of 'Rethink Binaries and Hierarchies' advocate for in the context of data feminism?
What does the principle of 'Rethink Binaries and Hierarchies' advocate for in the context of data feminism?
Data feminism advocates for 'Embracing Pluralism' This means...
Data feminism advocates for 'Embracing Pluralism' This means...
What is the key difference between the principles of 'Examine Power' and 'Challenge Power' in data feminism?
What is the key difference between the principles of 'Examine Power' and 'Challenge Power' in data feminism?
What is the core belief that underpins data feminism?
What is the core belief that underpins data feminism?
Flashcards
Data Feminism
Data Feminism
A framework merging feminist thought with data science to challenge power structures.
Examine Power
Examine Power
The principle of analyzing how power is distributed and influenced by data.
Challenge Power
Challenge Power
The commitment to confront and disrupt unequal power structures in data practices.
Rethink Binaries and Hierarchies
Rethink Binaries and Hierarchies
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Embrace Pluralism
Embrace Pluralism
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Core Principles of Data Feminism
Core Principles of Data Feminism
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Alternative Approaches
Alternative Approaches
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Equity in Data Practices
Equity in Data Practices
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Counterdata
Counterdata
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Dismantling Hierarchical Thinking
Dismantling Hierarchical Thinking
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Data Feminism Applications
Data Feminism Applications
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Marginalized Perspectives
Marginalized Perspectives
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Counterdata Importance
Counterdata Importance
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Rethinking Hierarchies
Rethinking Hierarchies
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Pluralism in Knowledge
Pluralism in Knowledge
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Study Notes
Data Feminism: Core Principles and Applications
- Data feminism is a framework combining intersectional feminist thought with data science to challenge unequal power structures and promote justice. It promotes gender equality, acknowledging that achieving equality requires addressing the root causes of inequalities faced by specific groups. Data feminism isn't solely focused on women; it encompasses working towards justice for all genders.
- It is a way of thinking about data, data systems, and data science, informed by feminist activism and critical thought.
Key Principles of Data Feminism
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Examine Power: Data feminism recognizes the unequal distribution of power in society and investigates how data science reinforces or challenges these existing power structures. This involves understanding how some groups wield disproportionate influence.
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Challenge Power: This principle aims to challenge unequal power structures toward justice. Actions include collecting counter-data, analyzing inequitable outcomes, envisioning alternative futures, and educating others about data feminism.
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Rethink Binaries and Hierarchies: Data feminism challenges binary systems – examples include the gender binary – and other classifications perpetuating oppression, seeking to dismantle hierarchical thinking and embrace more inclusive viewpoints.
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Embrace Pluralism: Data feminism values synthesizing multiple perspectives (including local, Indigenous, and experiential knowledge) for a deeper understanding, rejecting singular, objective truths. Diverse expertise is valued.
Data Feminism's Foundation
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Intersectional Feminist Thought: Data feminism is rooted in intersectional feminist thought, acknowledging interconnected struggles based on sex, race, sexuality, and class, highlighting how these intersect to create complex systems of power.
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Direct Experience: Recognizing data isn't neutral, but reflects societal inequalities.
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Commitment to Action: Data feminism promotes inclusive and representative data practices.
Data Feminism's Relevance to Data Science
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Data science can either uphold or challenge societal hierarchies.
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Data science often reflects societal biases due to limited perspectives in data collection and analysis, impacting minority and marginalized groups.
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The ethics of data collection, usage, and interpretation are growing concerns.
Case Study Examples
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MarÃa Salguero's Femicide Mapping: MarÃa Salguero (a human rights activist and geophysical engineer) mapped femicide instances to address gaps in official data.
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Detroit Geographic Expedition: This expedition mapped and addressed racial inequality in Detroit’s inner city, investigating injustices stemming from the 1967 riots. It documented and sought to address racial disparities within the city, highlighting that significant progress did not feel tangible to African Americans.
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