C. Taylor Brown

C. Taylor Brown

he/him

PhD Candidate in Social Welfare & Critical Theory | Ecosocial Policy & Climate Adaptation

Sitemap

A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.

Pages

Posts

Placeholder

less than 1 minute read

Published:

This post will show up by default. To disable scheduling of future posts, edit config.yml and set future: false.

portfolio

publications

We are the cure: How to help our democracy recover from the pandemic

Published in Gephardt Institute for Civic and Community Engagement, 2020

Recommended citation: Brown, C. T. (2020). We are the cure: How to help our democracy recover from the pandemic. Gephardt Institute for Civic and Community Engagement, https://gephardtinstitute.wustl.edu/university-wide-initiatives/this-civic-moment/thiscivicmomentseries/thiscivicmoment-taylor-brown/.
Download Paper

CLT Policy Playbook

Published in Center for Social Development, 2021

Recommended citation: Bandaru, S., Brown, C. T., Goldstein, E., Serwin, A., & Taylor P. (2021). CLT Policy Playbook. Center for Social Development.

Widowhood and mental health issues: Predictors of anxiety, depression, and PTSD among those who have been widowed

Published in Illness, Crisis & Loss, 2021

This study examines the relationship between three common mental health disorders—anxiety, depression, and post-traumatic stress disorder—in the first year of spousal bereavement and a myriad of social factors—including the security of health insurance and the presence of children at home—among those who have been widowed. We analyzed a novel survey of 503 widows who had participated in the Modern Widows’ Club Widows Empowerment Event. We then used logistic regression to investigate the relationship between these variables, discovering nuance between them. Our findings further elucidate the need for health and mental health providers to be attuned to the unique psychosocial needs of widows, especially among the first year of widowhood.

Recommended citation: Brown, C. T., & Harrold, J. (2021). Widowhood and mental health issues: Predictors of anxiety, depression, and PTSD among those who have been widowed. Illness, Crisis & Loss, 31(2). https://doi.org/10.1177/10541373211054189.
Download Paper

New opportunities from the Maryland Office of Statewide Broadband to connect your community to the internet

Published in CTC Technology & Energy, 2021

Recommended citation: Rivkin-Fish, Z., Fichman, B., & Brown, C. T. (2021, Jul. 8). New opportunities from the Maryland Office of Statewide Broadband to connect your community to the internet. CTC Technology & Energy, https://www.ctcnet.us/blog/new-opportunities-from-the-maryland-office-of-statewide-broadband-to-connect-your-community-to-the-internet/.
Download Paper

The politics of child welfare: Are child welfare policies, budgets and functioning a red/blue issue?

Published in Children and Youth Services Review, 2022

Child Protective Services (CPS) are a politically contentious area of practice and policy. While this is well known, no attempts have been made to understand differences in state level CPS systems as a function of state political orientation. We explore the bivariate and limited multivariate relationships between state political orientation (governorships, legislature and public voting patterns), CPS funding, the adoption of specific policies (differential response, drug policy, intimate partner violence policy, centralization and mandated reporting), system inputs (referral rate, percentage of reports from mandated sources, report types), and system outputs (percent screened in, percent substantiated and percent placed). We also explore the degree to which other state characteristics (wealth, rurality) are related to these outcomes. We find that political orientation has few associations with any of our dependent measures, and when present, such associations could plausibly related to state income and rurality measures, which did have consistent relationships to CPS functioning. Our approach found little indication that “Red” and “Blue” states differ markedly with regard to their CPS systems, and we include a series of suggestions for future research. We discuss the potential policy and practice implications of our findings.

Recommended citation: Brown, C. T., Ocampa, M. G., Drake, B. (2022). The politics of child welfare: Are child welfare policies, budgets and functioning a red/blue issue? Children and Youth Services Review, 132, 106282. 10.1016/j.childyouth.2021.106282.
Download Paper

Contextualization of transformative civic education

Published in Transformative Civic Education in Democratic Societies, 2023

Recommended citation: White, R., Brown, C. T., Pevits, A., & Martin, J. (2023). Contextualization of transformative civic education. In Hoggan-Kloubert, T., Mabrey III, P. E., & Hoggan, C. (eds.). Transformative Civic Education in Democratic Societies. Michigan State University Press: East Lansing, Michigan.

Civic education and social justice: Moving toward a pedagogy of community organizing and community-based participatory methods

Published in Transformative Civic Education in Democratic Societies, 2023

Recommended citation: Brown, C. T., White, R., Pevits, A., Martin, J. (2023). Civic education and social justice: Moving toward a pedagogy of community organizing and community-based participatory methods. In Hoggan-Kloubert, T., Mabrey III, P. E., & Hoggan, C. (eds.). Transformative Civic Education in Democratic Societies. Michigan State University Press: East Lansing, Michigan.

Comparative social policy

Published in Encyclopedia of Social Work, 2024

Recommended citation: Brown, C. T., & Gilbert, N. (2024). Comparative social policy. Encyclopedia of Social Work. https://doi.org/10.1093/acrefore/9780199975839.013.879.

Which side (of the balance sheet) are you on? Household financial resources and participation in the 2020 protests

Published in The Journal of Sociology & Social Welfare, 2024

The summer of 2020 was marked by widespread protests. Though research has often examined the predictors of protest participation, there exists little work examining the relationship between different types of wealth and protesting. Drawing on resource-based theories of protest participation and asset-based theories of civic engagement, we constructed regression models disentangling relationships between income, liquid assets, investment assets, homeownership, and protesting. Using a national survey administered during the protests, we find that liquid assets are negatively associated, homeownership is positively associated, and investment assets exhibit a non-linear association with protesting. These relationships hold when controlling for income, demographics, and ideology, but largely disappear when controlling for measures of economic vulnerability. These results are consistent across different protest types. Our work speaks to the role of protests as a means of political participation for economically marginalized groups and contributes to our knowledge of the intersection between economic indicators and political behaviors. Further, this work highlights how individual and contextual factors influence political behavior in varied ways, which has implications for protest organizers, civic engagement promoters, as well as policies aimed at protecting the right to protest.

Recommended citation: Miller, S., Roll, S., Brown, C. T., Brugger, L., & Grinstein-Weiss, M. (2024). Which side (of the balance sheet) are you on? Household financial resources and participation in the 2020 protests. The Journal of Sociology & Social Welfare, 50(4). https://doi.org/10.15453/0191-5096.4671.
Download Paper

The data science discovery program: A case for data science consulting in higher education

Published in Stat, 2024

As one of the largest data science research incubator initiatives in the country, the University of California, Berkeley’s Data Science Discovery Program serves as a case study for a scalable and sustainable model of data science consulting in higher education. This case contributes to the broader literature on data science consulting in higher education by analysing the programme’s development, institutional influences; staffing and structural model; and defining features, which may prove instructive to similar programmes at other institutions. The programme is characterised by a unique structure of undergraduate consultations led by graduate student mentorship and governance; a streamlined, multidepartmental model that facilitates scalability and sustainability; and diverse modes for undergraduate consulting—including one-on-one ad-hoc data science consultations, extended data science project development and management, peer mentorship and data science workshop instruction. This case demonstrates that universities may be able to initiate a low-stakes, small-scale data science consulting initiative and then progressively scale up the project in collaboration with multiple departments and organisations across campus.

Recommended citation: Brown, C. T., Mehta, M., Ryali, M., Dong, C., Shadfar, I., Dominquez Davalos, J., Culich, A., & Suen, A. (2024). The data science discovery program: A case for data science consulting in higher education. Stat, 13(2). http://doi.org/10.1002/sta4.677.
Download Paper

Limitations of ecomodernist climate change mitigation: The case of the U.S. Inflation Reduction Act and the (un)just transition

Published in Critical Social Policy, 2024

The US Inflation Reduction Act of 2022 marks a monumental shift toward mitigating climate change and transitioning to a clean energy society. With disproportionate, adverse impacts of climate change on marginalized communities, we utilize a critical environmental justice framework to investigate how the policy structure may deepen social inequalities. While the climate policy invests in clean energy and includes provisions for marginalized communities, our critical analysis finds embedded, conventional power imbalances ceded to corporations and a failure to acknowledge environmental racism. As a result, benefits are far from equitably distributed to communities that bear class, racial, and environmental burdens. We specify policy revisions of narrowing low-income eligibility, incorporating race in provisional criteria, and expanding clean energy investments to environmental justice locations. While our proposed reforms may create a more equitable response, we argue US climate policy’s shortcomings are endemic to its ecomodernist approach, limiting the possibility of a just transition.

Recommended citation: Grounder, B., & Brown, C. T. (2024). Limitations of ecomodernist climate change mitigation: The case of the U.S. Inflation Reduction Act and the (un)just transition. Critical Social Policy. http://dx.doi.org/10.1177/02610183241281349.
Download Paper

Welfare regime typologies: The six worlds of social inclusion.

Published in Journal of International and Comparative Social Policy, 2024

This study bridges the study of social inclusion with welfare regime theory. By linking social inclusion with welfare regimes, we establish a novel analytical framework for assessing global trends and national divergences in social inclusion based on a multidimensional view of the concept. While scholars have developed typologies for social inclusion and welfare regimes independent of each other, limited insights exist on how social inclusion relates to welfare regime typologies. We develop a social inclusion index for 225 countries using principal component analysis with 10 measures of social inclusion from the United Nations’ Sustainable Development Goals Indicators Database. We then employ clustering algorithms to inductively group countries based on the index. We find six “worlds” of social inclusion based on the index and other social factors – the Low, Mid, and High Social Inclusion regimes and the Low, Mid, and High Social Exclusion regimes.

Recommended citation: Brown, C. T., & Ben Brik, A. (in press). Welfare regime typologies: The six worlds of social inclusion. Journal of International and Comparative Social Policy.

Ecosocial policy and the social risks of climate change: Foundations of the U.S. ecosocial safety net

Published in Journal of Social Policy, 2024

As climate change progresses, natural hazards are projected to continue to increase in frequency and intensity, posing a new form of social risk, implicating both the welfare and environmental state and raising the salience of ecosocial policy as a mechanism to attend to the distributional effects of climate change mitigation and adaptation. This study posits a novel conceptual framework for ecosocial policy and offers the US ecosocial safety net as a case analysis. While we conceptualise disaster relief policy as a mode of the environmental state, it includes unique ecosocial policies that constitute the backbone of the US ecosocial safety net. This study describes and compares the developmental and functional synergies between the US welfare and environmental state manifested in the form of an ecosocial safety net by explicating the Individual Assistance Program and the National Flood Insurance Program. Our findings reveal synergies between US disaster relief and welfare, including parallel developmental trends, philosophies of deserving/undeserving, functions of racial capitalism and relationships with economic growth. This study and its conceptual framework of ecosocial policy offer a groundwork for the study of ecosocial policy in other contexts.

Recommended citation: Brown, C. T., & Chang, Y. L. (2024). Ecosocial policy and the social risks of climate change: Foundations of the U.S. ecosocial safety net. Journal of Social Policy. https://doi.org/10.1017/S0047279424000126.
Download Paper

Practitioner perspectives on disaster assistance reform: A roadmap of obstacles to avoid

Published in Center for Emergent Disaster Resilience, 2025

Recommended citation: Davidson, T., Brown, C. T., Rathbun, H., Jerolleman, A., Awbrey, M., Guerke, M., Leahy, C., Feliscar, L., Logan, A., Patton, N., & Ferreira, R. (2025). Practitioner perspectives on disaster assistance reform: A roadmap of obstacles to avoid. Full report—Part I of III. Consortium for Emergent Disaster Resilience. https://cedrhub.org/publications/.

What is environmental justice?

Published in Introduction to Social Justice, 2025

Recommended citation: Hamilton, G., & Brown, C. T. (2025). What is environmental justice? In Rogerson, C., & Vandergrift, K. F. (eds.). Introduction to social justice. Solana Beach: Cognella.

Temporary measures or lasting reform? Examining Gulf States’ evolving welfare policies in response to the global health crisis

Published in Social Policy & Society, 2025

The global health crisis prompted Arabian Gulf states to implement extensive social protection measures to address public health and economic challenges. This study critically examines welfare reforms enacted by six Gulf countries – Saudi Arabia, UAE, Kuwait, Bahrain, Qatar, and Oman – through the theoretical lenses of Welfare Regime Theory and Punctuated Equilibrium Theory. Initially, governments temporarily expanded exclusion-based welfare systems, primarily benefiting citizens, to support broader populations, including migrant workers. However, the long-term sustainability of these expansions remains uncertain. The findings suggest that although the crisis created a temporary policy window for welfare expansion, there was no fundamental reconfiguration of these exclusionary welfare regimes. This study enhances the understanding of the adaptability of Gulf welfare states during global crises and the potential for future policy shifts.

Recommended citation: Ben Brik, A., & Brown, C. T. (2025). Temporary measures or lasting reform? Examining Gulf States’ evolving welfare policies in response to the global health crisis. Social Policy & Society, First Look, 1-25. https://doi.org/10.1017/S1474746424000630.
Download Paper

Welfare regime typologies: The six worlds of social inclusion

Published in Journal of International and Comparative Social Policy, 2025

This study bridges the study of social inclusion with welfare regime theory. By linking social inclusion with welfare regimes, we establish a novel analytical framework for assessing global trends and national divergences in social inclusion based on a multidimensional view of the concept. While scholars have developed typologies for social inclusion and welfare regimes independent of each other, limited insights exist on how social inclusion relates to welfare regime typologies. We develop a social inclusion index for 225 countries using principal component analysis with 10 measures of social inclusion from the United Nations’ Sustainable Development Goals Indicators Database. We then employ clustering algorithms to inductively group countries based on the index. We find six “worlds” of social inclusion based on the index and other social factors – the Low, Mid, and High Social Inclusion regimes and the Low, Mid, and High Social Exclusion regimes.

Recommended citation: Brown, C. T., & Ben Brik, A. (2025). Welfare regime typologies: The six worlds of social inclusion. Journal of International and Comparative Social Policy. https://doi.org/10.1017/ics.2024.14.
Download Paper

A critical review of conceptualization and measurement of social inclusion: Directions for conceptual clarity

Published in Social Policy & Society, 2025

We apply a synthesis review to revisit the concept, measurement, and operationalisation of social inclusion and exclusion in the context of comparative social policy, integrating the vast literature on the concepts, with the aim of elucidating a clearer understanding of the concepts for use by scholars and policymakers around the planet. In turn, we outline the conceptual development of the concepts, how they have been operationalised through social policy, and how they have been measured at the national and individual levels. Through our review, we identify limitations in extant conceptualisation and measurement approaches and suggest directions for refining conceptual and measurement frameworks to enhance their utility in social inclusion policy, emphasising the concepts’ multidimensional, multilevel, dynamic, and relational essence and highlighting their connection to related concepts such as social capital, social integration, and social citizenship.

Recommended citation: Brik, A. B., & Brown, C. T. (2025). A critical review of conceptualization and measurement of social inclusion: Directions for conceptual clarity. Social Policy and Society, First View, 1-14. https://doi.org/10.1017/S1474746425000302.
Download Paper

Ecosocial adaptation and the care professions: A systems-ecological approach to climate risk

Published in Social Work in Public Health, 2025

As climate change accelerates, it generates not only environmental disruption but a new form of multidimensional social risk – climate risk – unfolding across nested social, ecological, and institutional systems. This paper advances a systems-ecological perspective to conceptualize climate risk as a relational and stratified risk, disproportionately impacting marginalized communities. It then maps dominant adaptation frameworks – ecomodernism, post-/degrowth, sustainability, Indigenous knowledge, and environmental and climate justice, as well as environmental social work – highlighting their divergent assumptions, values, and implications for equity and resilience. Building on these perspectives, the paper introduces the concept of ecosocial adaptation, an integrative framework that foregrounds inclusion, care systems, and ecological interdependence as central to climate resilience. Care professions like social work, public health, education, and allied fields are already engaged in adaptation, yet often without a shared paradigm. This paper calls for the care professions to embrace ecosocial adaptation as a unifying framework to guide practice, pedagogy, and policy, positioning them as critical agents in climate adaptation.

Recommended citation: Brown, C. T. (2025). Ecosocial adaptation and the care professions: A systems-ecological approach to climate risk. Social Work in Public Health, 1-15. https://doi.org/10.1080/19371918.2025.2554664.
Download Paper

Contradictions of the ecowelfare state: The state, the human, and nature

Published in Capitalism Nature Socialism, 2025

This paper theorizes ecowelfare as the arena in which the capitalist state governs co-produced crises of climate change and inequality by adding a third regulatory imperative—ecoregulation—to accumulation and legitimation. Read through metabolic rift and world-ecology, ecoregulation is the ongoing (re)composition of human–nature relations via discursive, administrative, and material techniques—eco(de/re)commodification. Deployed heuristically, this lens surfaces three recurrent contradictions: legitimation, as programs stabilize human/nature binaries even as lived experience erodes them; accumulation, as carbonized, commodified need-satisfaction forecloses sufficiency; and scale/time, as national policies mismatch planetary dynamics. U.S. cases—FEMA’s Individual Assistance Program and the National Flood Insurance Program—show how eligibility, mapping, and pricing humanize and exclude. The paper proposes evaluative criteria and sketches ecosocial designs that reorient crisis governance.

Recommended citation: Brown, C. T. (2025). Contradictions of the ecowelfare state: The state, the human, and nature. Capitalism Nature Socialism. https://doi.org/10.1080/10455752.2025.2587871.
Download Paper

Hotspots of inequity in climate adaptation: Explaining the stratification of U.S. ecowelfare using space-time and machine learning analysis

Published in Climate, 2025

As climate risk intensifies and ecowelfare is increasingly implicated in climate adaptation, we examine how FEMA’s Individuals and Households Program (IHP) allocates aid in the United States. We ask how and why IHP allocates aid, framing the analysis through a climate-justice lens that centers distributive and procedural equity. Using a county–year panel (2009–2022), we map funding hot/cold spots and estimate space–time models of per-recipient IHP funding, benchmarking against machine learning approaches. Results show that aid rises with a county’s own disaster frequency but falls when neighboring counties are simultaneously hit. Direct sociodemographic penalties are limited once space–time dependence is modeled, except for a persistent shortfall in counties with larger multiracial populations and a negative neighboring effect tied to Hispanic composition. Poverty and population size show positive neighboring effects, and counties in Democratic-governed states receive more aid, consistent with higher state capacity. Machine learning corroborates hazards’ primacy and highlights disaster-count thresholds and interactions. Implications for climate justice and adaptation include strengthening regional capacity, expanding language-access and navigator programs that help households apply for aid, and adopting local-national coordination standards to make ecowelfare more equitable and resilient.

Recommended citation: Brown, C. T. & Chang, Y. L. (2025). Hotspots of inequity in climate adaptation: Explaining the stratification of U.S. ecowelfare using space-time and machine learning analysis. Climate, 13(12), 244. https://doi.org/10.3390/cli13120244.
Download Paper

Computational social policy

Published in Elgar Research Encyclopedia of Social Policy, 2026

Recommended citation: Brown, C. T. (in press). Computational social policy. In Aspalter, C. (ed.), Elgar Research Encyclopedia of Social Policy. Edward Elgar.

Ecosocial policy

Published in Elgar Research Encyclopedia of Social Policy, 2026

Recommended citation: Brown, C. T. (in press). Ecosocial policy. In Aspalter, C. (ed.), Elgar Research Encyclopedia of Social Policy. Edward Elgar.

United States: An evolving liberal welfare state—deepening workfare and fragmentation

Published in Worlds of Welfare: Comparing Safety Nets Across the Globe, 2026

Recommended citation: Chang, Y. L., & Brown, C. T. (in press). United States: An evolving liberal welfare state—deepening workfare and fragmentation. In Wang J. S.-H. & Marx, I. (eds.), Worlds of Welfare: Comparing Safety Nets Across the Globe, Cheltenham: Edward Elgar Publishing.

A scoping literature review on FEMA’s Individuals and Households Program

Published in , 2026

Recommended citation: Awbrey, M., Davidson, T., Feliscar, L., Rathbun, H., Brown, C. T., Ferreira, R. J., Leahy, C., Jerolleman, A., Logan, A., Guerke, M., Contillo, C. M., Bamba, L. A. M., Vermilyea, J., Rose, K., & Buttell, F. P. (under review). A scoping literature review on FEMA’s Individuals and Households Program.

Fueling ecowelfare: A global comparative analysis of energy and utility assistance

Published in Social Policy & Administration, 2026

Recommended citation: Brown, C. T., Wang, J., Chang, Y.-L., Lucuix, M. B., Krmpotic, C., dos Santos Ronzoni, R., Prá, K. R. D., Peng, N., Henley, J., Lee, Y. Kajai, S., Cho, S., Colin, S., & Rodriguez, R. (under review). Fueling ecowelfare: A global comparative analysis of energy and utility assistance. Accepted Special Issue with Social Policy & Administration.

talks

teaching

Seminar

Field Liason, Undergraduate Course, Harding University, School of Social Work, 2021

SWK 4510 - Review of latest developments in social work; analysis of problems encountered in field placement; development of self-awareness and individual worker style.

Field Placement

Field Liason, Undergraduate Course, Harding University, School of Social Work, 2021

SWK 4520 - Placement in a social work agency for 420 hours of supervised field practice.

Social Work Research

Adjunct Professor, Undergraduate Course, Harding University, School of Social Work, 2021

SOC 3300 - Study of the research process and its applications in generalist social work practice. Conceptual foundation for research. Quantitative and qualitative methods of inquiry, design, data collection and analysis. Ethical and human diversity issues in research.

General Sociology

Adjunct Professor, Undergraduate Course, Harding University, School of Social Work, 2021

SOC 2030 - A broad perspective of the nature of society and its problems in terms of social institutions, forces, and changes. Cultural diversity and understanding of group interaction in our multi-ethnic society.

General Sociology

Adjunct Professor, Undergraduate Course, Harding University, School of Social Work, 2022

SOC 2030 - A broad perspective of the nature of society and its problems in terms of social institutions, forces, and changes. Cultural diversity and understanding of group interaction in our multi-ethnic society.

Seminar

Field Liason, Undergraduate Course, Harding University, School of Social Work, 2022

SWK 4510 - Review of latest developments in social work; analysis of problems encountered in field placement; development of self-awareness and individual worker style.

Field Placement

Field Liason, Undergraduate Course, Harding University, School of Social Work, 2022

SWK 4520 - Placement in a social work agency for 420 hours of supervised field practice.

Poverty and Economic Justice

Graduate Student Instructor, Undergraduate Course, University of California, Berkeley, School of Social Welfare, 2023

SOCWEL 116 - Course examines current problems and issues in the field of social welfare.

Seminar in Social Welfare Research

Graduate Student Instructor, Graduate Course, University of California, Berkeley, School of Social Welfare, 2024

SOCWEL 282B - This course provides an overview on techniques for and challenges in program evaluation. Students will develop the critical skills necessary to assess the quality of evaluation research projects, to apply technical evaluation skills in professional practice, and to develop evaluation plans for a variety of programs. Students will apply the knowledge of research methods acquired through the MSW program to develop a program evaluation plan. Special attention will be paid to participatory, collaborative and equitable evaluation approaches, as well as qualitative methods. Through this course, each student will develop a program evaluation plan for a program of their choice.

Institutional Review Board Fundamentals

Instructor, Workshop, University of California, Berkeley, Social Sciences Data Laboratory, 2024

This course will walk you through the process of getting IRB approval for your project.

R Fundamentals

Instructor, Workshop, University of California, Berkeley, Social Sciences Data Laboratory, 2024

This interactive workshop series is your complete introduction to programming in R for people with little or no previous programming experience. It covers the basics of using RStudio, creating variables, working with data frames, and starting to analyse your data using summary statistics and data visualization.

Python Fundamentals

Instructor, Workshop, University of California, Berkeley, Social Sciences Data Laboratory, 2024

This six-part interactive workshop series is your complete introduction to programming Python for people with little or no previous programming experience, with a focus on data science application. In Parts 1-3, we cover the basics of Python and Jupyter, variables and data types, and a gentle introduction to data analysis in Pandas. In Parts 4-6, we cover loops and conditionals, creating your own functions, analysis and visualization in Pandas, and the workflow of a data science project.

Python Data Wrangling

Instructor, Workshop, University of California, Berkeley, Social Sciences Data Laboratory, 2024

In this workshop, we provide an introduction to data wrangling with Python. We will do so largely with the pandas package, which provides a rich set of tools to manipulate and interact with data frames, the most common data structure used when analyzing tabular data. We’ll learn how to manipulate, index, merge, group, and plot data frames using pandas functions.

Python Web Scraping

Instructor, Workshop, University of California, Berkeley, Social Sciences Data Laboratory, 2024

In this workshop, we cover how to scrape data from the web using Python. Web scraping involves downloading a webpage’s source code and sifting through the material to extract desired data.

Machine Learning in Python

Instructor, Workshop, University of California, Berkeley, Social Sciences Data Laboratory, 2024

In this workshop, we provide an introduction to machine learning in Python. First, we’ll cover some machine learning basics, including its foundational principles. Then, we’ll dive into code, understanding how to perform regression, regularization, preprocessing, and classification. There are additional components of the workshop which explore building machine learning pipelines and unsupervised learning. We’ll demonstrate how to perform these tasks using scikit-learn, the main package used for machine learning in Python.

Python Fundamentals

Instructor, Workshop, University of California, Berkeley, Social Sciences Data Laboratory, 2024

This six-part interactive workshop series is your complete introduction to programming Python for people with little or no previous programming experience, with a focus on data science application. In Parts 1-3, we cover the basics of Python and Jupyter, variables and data types, and a gentle introduction to data analysis in Pandas. In Parts 4-6, we cover loops and conditionals, creating your own functions, analysis and visualization in Pandas, and the workflow of a data science project.

Python Data Wrangling

Instructor, Workshop, University of California, Berkeley, Social Sciences Data Laboratory, 2024

In this workshop, we provide an introduction to data wrangling with Python. We will do so largely with the pandas package, which provides a rich set of tools to manipulate and interact with data frames, the most common data structure used when analyzing tabular data. We’ll learn how to manipulate, index, merge, group, and plot data frames using pandas functions.

Python Data Visualization

Instructor, Workshop, University of California, Berkeley, Social Sciences Data Laboratory, 2024

In this workshop, we provide an introduction to data visualization with Python. First, we’ll cover some basics of visualization theory. Then, we’ll explore how to plot data in Python using the matplotlib and seaborn packages.

Social Welfare Policy

Graduate Student Instructor, Undergraduate Course, University of California, Berkeley, School of Social Welfare, 2025

SOCWEL 112 - Analysis of social welfare policies and programs including public assistance, social insurance, social services, and health and mental health.

R Fundamentals

Instructor, Workshop, University of California, Berkeley, Social Sciences Data Laboratory, 2025

Python Machine Learning Fundamentals

Instructor, Workshop for UC Berkeley Master of Computational Social Science, University of California, Berkeley, Social Sciences Data Laboratory, 2025

GPT Fundamentals

Instructor, Workshop for UC Berkeley Master of Computational Social Science, University of California, Berkeley, Social Sciences Data Laboratory, 2025

Python Web APIs

Instructor, Workshop, University of California, Berkeley, Social Sciences Data Laboratory, 2025

Python Web Scraping

Instructor, Workshop, University of California, Berkeley, Social Sciences Data Laboratory, 2025

Python for Business Leaders

Instructor, Workshop for UC Berkeley Masters in Business Administration Program, University of California, Berkeley, Social Sciences Data Laboratory, 2025

R Fundamentals

Instructor, Workshop, University of California, Berkeley, Social Sciences Data Laboratory, 2025

R for Public Health

Instructor, Workshop, University of California, Berkeley, Social Sciences Data Laboratory, 2025

AI Assisted Coding in R

Instructor, Workshop, University of California, Berkeley, Social Sciences Data Laboratory, 2025

Social Welfare Policy

Graduate Student Instructor, Undergraduate Course, University of California, Berkeley, School of Social Welfare, 2025

SOCWEL 112 - Analysis of social welfare policies and programs including public assistance, social insurance, social services, and health and mental health.

Python Fundamentals

Instructor, Workshop, University of California, Berkeley, Social Sciences Data Laboratory, 2025

Research and Evaluation

Instructor, Graduate Course, Tulane University, Disaster Resilience Leadership Academy & School of Social Work, 2026

AI-Assisted Coding in R

Instructor, Workshop, University of California, Berkeley, Social Sciences Data Laboratory, 2026

Python Fundamentals

Instructor, Workshop, University of California, Berkeley, Social Sciences Data Laboratory, 2026

R for Public Health

Instructor, Workshop, University of California, Berkeley, Social Sciences Data Laboratory, 2026