Structural Intersectional Theory.pdf

Structural Intersectional Theory
Aashish Juneja Ph.D
Solving Problems with Technology & Psychology
Advancing cross disciplinary research in Positive Psychology, Artificial Intelligence & Corporate Governance

What is Structural
Intersectional
Theory
2
 Structural Intersectional Theory is a framework
that builds upon the concepts of both
structural theory and intersectionality.
 It seeks to understand and analyze the complex
interplay of social structures, such as race,
class, gender, sexuality, disability, and other
dimensions of identity, within the broader
context of systemic oppression and privilege.
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Key Components
of Structural
Intersection
Theory
3

1. Intersectionality
4
Intersectionality: Idea that individuals possess multiple social
identities (e.g., race, gender, class) that interact to shape their
experiences of privilege & oppressions.
Structural Intersectional Theory takes this concept further by
examining how these intersecting identities are embedded within
and influenced by larger social structures.
Prof Kimberl’e Cresnshaw, image Credit Wiki
https://www.law.columbia.edu/faculty/kimberle-
w-crenshaw Aashish Juneja Ph.D
Developed by Kimberlé Crenshaw, Professor of Law at Columbia University. She
studied the double bind of simultaneous racial & gender prejudice.

2. Social
Structures
5
Social Structures: Structural Intersectional Theory
emphasizes the role of social structures,
institutions, and systems in shaping and
perpetuating inequalities.
It looks at how power, resources, and
opportunities are distributed within society and
how different groups are situated within these
structures.
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3. Multiple axis of
identity
6
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generated by DELL-E
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3. Multiple Axis of Identity
7
Multiple Axes of
Identity: This theory
recognizes that
people's identities
cannot be reduced to
a single dimension
(e.g., gender or race).
01
Instead, individuals
have multiple
identities that
intersect and can lead
to unique experiences
of privilege and
oppression.
02
For example, a Black
woman may face
different challenges
compared to a White
woman or a Black
man due to the
intersection of race
and gender.
03

4. Complexity & Fluidity
8
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Juneja , image generated by DELL-E Aashish Juneja Ph.D

4. Complexity & Fluidity
9
Complexity and Fluidity: Structural Intersectional
Theory acknowledges the complexity and fluidity of
identity.
It understands that identities can change over time, and
individuals may shift between positions of privilege and
disadvantage depending on various factors and
contexts.

5. Social Change & Activism
10
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5. Social Change & Activism
Social Change and Activism: This framework often aligns
with social justice movements and activism.
It calls for a comprehensive understanding of the
interconnected systems of oppression to inform strategies for
dismantling them.
Advocates of Structural Intersectional Theory argue for inclusive
and equitable policies and practices that address the unique
experiences of marginalized groups.
11

6. Interdisciplinary Nature
of Structural Intersection theory
12
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by DELL-E Aashish Juneja Ph.D

6. Interdisciplinary Nature
Interdisciplinary Approach: To fully understand the
intersection of social structures and identities, this theory
often draws from multiple disciplines, including
sociology, anthropology, psychology, and critical theory.
Scholars and activists from various fields collaborate to
explore the multifaceted nature of inequality.
13

Structural
Intersection theory
contradicts
Essentialism
Structural Intersection theory
challenges Essentialism.
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generated by DELL-E
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6. Rival framework to Essentialism
Critique of Essentialism: Structural Intersectional
Theory challenges essentialist thinking, which reduces
people to one defining characteristic or identity.
Instead, it recognizes that people's experiences are shaped
by a multitude of factors and that oversimplification can
hinder a nuanced understanding of inequality.
15

In Summary
Structural Intersectional
Theory extends the concept of
intersectionality by integrating
it with structural analysis.
It helps us grasp the intricate ways in
which social structures and intersecting
identities contribute to systemic
inequalities and informs efforts to create
a more just and equitable society.
16

Why Artificial Intelligence
for Structural
Intersectional Theory
Research
17
AI is offering new ways to analyze complex
social systems, identify patterns, and draw
insights from large datasets

Use Cases of AI in Structural Intersection theory
research
1. Bias Detection & Mitigation
 AI tools can be used to detect and mitigate bias in
research datasets.
 This can ensure that data used in structural
intersectionality research is representative and
free from biases that could reinforce existing
inequalities.
2. Data Analysis & Pattern
Research
 AI can help researchers analyze large datasets to
identify patterns, relationships, and disparities
within and across various social dimensions.
 AI can help uncover hidden connections and trends
related to intersectional identities.
18

Use Cases of AI in Structural Intersection
Theory Research
3. Reverse Causality Problem
 AI can help control for confounding variables
and understand complex causal relationships.
intersectionality research is representative
and free from biases that could reinforce
existing inequalities.
4. Predictive Modeling
 Create predictive models for outcomes
related to structural intersectionality.
 Use case 1. Predicting the impact of policy
changes on marginalized communities
 Use case 2: Assessing the likelihood of
experiencing discrimination based on
intersecting identities.
19

Use Cases of AI in Structural Intersection
Theory Research
5. Simulation & Scenario
Analysis
 AI can enable researchers to build simulation
models that explore the effects of structural
changes and interventions on different
intersectional groups.
 Use case 1: Designing and evaluating policies to
address inequalities.
 Use case 2: Ensemble forecasting of likely impact
of interventions aimed to address systemic
inequalities.
intersectionality research is representative and
free from biases that could reinforce existing
inequalities.
6. Visualization & Data
Interpretation
 Communicate research findings effectively with
AI- powered data visualization tools for
interactive & informative visualizations that
convey complex intersectional concepts to wider
audience.
 Use case : Examining educational disparities
among marginalized communities based on the
intersection of region (rural/urban), gender, and
socioeconomic status and caste.
 Interactive heat map to display educational outcomes based on
combinations.
 Cluster analysis – grouping demographics with similar
educational outcomes.
 Natural language generator to generate plain language
explanations and insights based on data.
20

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