Technocratic or Democratic? How Data Cultures Shape Success, Decision-Making, and Accountability in School Board Governance

• In Event: A Critical Examination of School Board Governance Models: Imagining a Better Future

Abstract

Purpose
School boards across the United States are increasingly adopting governance models such as Student Outcomes Focused Governance, Empowered Governance, and Balanced Governance that aim to improve board effectiveness by aligning decisions with equity goals and student outcomes. While these models emphasize data use to define success and guide decision-making, the underlying assumptions, or data logics, that shape how evidence is used are understudied. We examine how data practices embedded within these models construct definitions of success, shape board decision-making, and legitimize particular forms of evidence and authority.


Perspectives
We ground this study in QuantCrit, which interrogates the racialized and political nature of statistical data production, interpretation, and use (Castillo & Gillborn, 2022; Garciá et al., 2018; Zuberi & Bonilla-Silva, 2008). While most commonly applied to quantitative analysis, we extend QuantCrit to examine how racialized data logics (Zuberi & Bonilla-Silva, 2008) operate within school board governance, shaping how school board members define success, legitimize certain forms of data, and make decisions. Guided by QuantCrit tenets, we analyze how equity-framed data practices often reinforce objectivity and performance logics (Stage, 2007), obscure context, reify racialized categories (Pérez Huber et al., 2018), and privilege white normative standards (Bonilla-Silva & Zuberi, 2008; Zuberi, 2003).

Methods and Data Sources
As part of a multi-phase project on school board governance, we conducted a qualitative analysis of publicly available materials across three governance models. Data sources included training materials, strategic plans, superintendent evaluation rubrics, media coverage, and semi-structured interviews with governance model developers and school board members. Using theoretical coding, we examine how data practices are embedded in each model and shape board members’ interpretations of evidence, equity, and accountability.

Preliminary Findings
Our analysis reveals that while all three governance models articulate commitments to equity, their data practices frequently emphasize test scores and narrow performance indicators. As one participant noted, “...standardized testing is the necessity. Whether it's grounded in state or federal or local capture, that's a board decision. It would be irresponsible for the board to be making decisions without standardized data.” These data logics reflect dominant accountability frameworks that prioritize standardized metrics, potentially marginalizing community-based knowledge and alternative indicators of student success. Across models, we identify three distinct data cultures, each advancing different definitions of success and shaping who holds power, whose perspectives are valued, and how decisions are made in school board governance.


Significance
We extend QuantCrit beyond methodological critique to examine how data practices in school board governance shape power and decision-making. We theorize data cultures as historically rooted and consequential, revealing how embedded logics narrow what counts as evidence and whose knowledge is valued. In line with the AERA 2026 theme, we envision futures where data are equity-centered, community-anchored, and challenge dominant metrics, uplifting the lived experiences and expertise of historically marginalized communities.

Authors

• Lolita A. Tabron, University of Denver

• John Matthew Fredericks, Arizona State University

• Ashley Yung Batchelor, Arizona State University