Nice Data, Now Show Me the Human Story Behind These Numbers!

Reynold V. Galope, PhD, MPP

Reynold V. Galope, PhD, MPP
2023-2024 American Evaluation Association (AEA) MSI Fellow
Associate Professor of Public and Nonprofit Administration
MPNA/MPA/MNLM Graduate Program Director
College of Community Studies and Public Affairs
Metropolitan State University

Nice Data, Now Show Me the Human Story Behind These Numbers!
Reynold V. Galope, PhD, MPP
AEA365 blog post, 2024

Can data alone tell the complete story of a program’s impact? In his recent AEA365 blog post, “Nice Data, Now Show Me the Human Story Behind These Numbers!”, Dr. Reynold Galope challenges evaluators to think critically about the relationship between quantitative data and the lived experiences of program participants. He reflects on how his approach to program evaluation has evolved, particularly through his engagement with Culturally Responsive and Equitable Evaluation (CREE), where the limitations of numbers are often brought into sharp focus.

Dr. Galope emphasizes that while data such as Average Treatment Effects (ATE) are valuable, they can mask disparities and fail to capture the complex, intersecting identities of program beneficiaries. To truly understand a program’s effectiveness, evaluators must go beyond the numbers and delve into the stories and experiences of the people behind them. This human-centered approach allows for deeper insights into program mechanisms and outcomes, providing a more holistic understanding of how well a program serves diverse communities. Dr. Galope’s blog encourages readers to reconsider traditional methods of evaluation and adopt a more inclusive perspective.

More about the AEA MSI Fellowship

The American Evaluation Association’s (AEA) MSI Fellowship is designed to bring together faculty from Minority Serving Institutions (MSIs) for professional development, networking, and training in evaluation and research. The program seeks to increase participation from underrepresented groups in the evaluation field, offering participants workshops, webinars, and mentoring to broaden their understanding of evaluation as a profession. Additionally, the fellowship aims to enhance evaluation activities at MSIs, orient students to evaluation careers, and encourage cross-disciplinary collaboration and writing. For more details, visit AEA MSI Fellowship.

More about Culturally Responsive and Equitable Evaluation (CREE)

Culturally responsive and equitable evaluation (CREE) requires the integration of diversity, inclusion, and equity in all phases of evaluation. CREE incorporates cultural, structural, and contextual factors (e.g., historical, social, economic, racial, ethnic, gender) using a participatory process that shifts power to individuals most impacted. CREE is not just one method of evaluation, it is an approach that should be infused into all evaluation methodologies. CREE advances equity by informing strategy, program improvement, decision-making, policy formation, and change.

Rey Galope is an Associate Professor in the College of Community Studies and Public Affairs (CCSPA) at Metropolitan State University (Saint Paul, MN), where he teaches program evaluation, policy analysis, economic reasoning, and applied research methods and statistics to public and nonprofit professionals, including data and policy analysts, program evaluators, and social change advocates.

Rey received his Ph.D. in Public Policy from Georgia State University (Andrew Young School of Policy Studies) and the Georgia Institute of Technology (School of Public Policy) as a Fulbright Scholar and his Master of Public Policy (MPP) from the Lee Kuan Yew School of Public Policy of the National University of Singapore (NUS) as a Temasek Scholar. His graduate training in econometrics and quantitative methods influenced much of his prior program evaluation work. His evaluation of the certification and additionality effects of the Small Business Innovation Research (SBIR) Program, a federal program that co-finances R&D with promising small businesses, used propensity score matching to improve homogeneity between treated and untreated groups, and his most recent work investigating the impact of online teaching on student learning exploited a natural experiment to make the ignorability of treatment assignment assumption more plausible.