From Conference Presentation to Ethical Representation: Reimagining Our Research Responsibilities at AERA

Last Friday at the American Educational Research Association (AERA) conference in Denver, I participated in the 28th Conversations with Senior Scholars, chaired by Dr. Hank Frierson. Alongside Dr. Timothy Eatman and Dr. Shaun Harper, I led a discussion on advancing academic success for Black students through research.

During our exchange, a recent doctoral graduate asked a question: given today's politically charged climate surrounding diversity, equity, and inclusion efforts, how should she represent her findings? Behind her question lay a deeper anxiety about responsibility—to her data, her participants, and the communities her work might impact.

What began as a single question evolved into a rich dialogue about representation itself. Not just statistical representation, but ethical representation. I realized how this mirrors what I see in my own students, who've been trained to prioritize disciplinary conventions and methodological orthodoxy over their responsibility to the people whose lives they study. They've learned to speak first for their field, then for their participants.

To reframe this relationship, I offered a simple analogy: What if researchers represented their participants the way attorneys represent clients?

Dr. Harper immediately strengthened this idea, noting that when we seek legal representation, we don't want detached objectivity—we want vigorous advocacy. We want someone firmly in our corner, using every ethical means to ensure our voice is heard and our interests protected.

This conversation continued to resonate with me long after we adjourned. The lawyer-client model provides a clarifying framework for research ethics that I've circled around before but never articulated quite so directly. In today's contested research environment, it offers a compelling alternative to the myth of dispassionate objectivity.

The Journey to a New Understanding

Throughout my career in educational research, I've confronted the limitations of what we call "objectivity." I've observed talented researchers who discover compelling evidence of systemic inequities yet hesitate to directly name what they've found. Instead, they retreat behind technical language and statistical jargon. This pattern appears especially pronounced among scholars from Socially, Culturally, and Economically Diverse (SCED) communities, who often feel pressured to present themselves as detached observers even when studying issues that directly affect their own communities and lived experiences.

This pressure reveals a profound double standard in academia that I've previously addressed:

"White privilege enables White researchers to claim authority on Black issues, while questioning the ability of Black people to conduct objective research" (Toldson, 2019, p. 63).

This asymmetry allows some scholars to speak confidently about communities they don't belong to, while researchers from those same communities must constantly prove their objectivity and defend their scholarly credibility.

On my flight home from Denver, I kept returning to a fundamental question: What if we fundamentally reconsidered the researcher-participant relationship?

Traditional statistical training presents representation primarily as a technical problem to solve through proper sampling methods, randomization procedures, and variable control. This approach has value but overlooks something crucial: statistical representation is inherently incomplete. Even the most methodologically sound sample cannot fully capture the complexity and nuance of human experience. Data points require context. Numbers need interpretation. Statistics demand meaning that comes from understanding the lived realities behind the figures.

The Legal Advocacy Model: A Clear Parallel

Consider what we expect from legal representation. When you hire an attorney, you don't want someone who equivocates about your case, saying, "My client might be innocent, or perhaps guilty—I'm simply presenting the facts neutrally." You expect your lawyer to advocate vigorously for your interests while remaining truthful and ethical. This was precisely the point Dr. Harper emphasized during our Denver discussion.

Yet in research, we've constructed a strange paradox. We collect data from communities, analyze their experiences, and claim to represent their realities—but then deliberately distance ourselves from advocating for those same communities when presenting our findings.

This contradiction became clear to me while mentoring a doctoral candidate researching school discipline practices. Her data revealed striking patterns: Black boys in middle schools received significantly harsher punishments than their white peers for identical infractions. Her evidence was methodologically sound and statistically significant.

Yet throughout her dissertation draft, she consistently used passive constructions: "Disparities were observed..." "Differences were noted..."

"Who observed these disparities?" I asked during a revision session.

She looked confused. "I did."

"Then why not say so? You documented this injustice carefully and systematically. Why present yourself as an invisible observer?"

Her response was revealing: "I was taught that objective research requires this kind of language."

"Let's consider who benefits from this particular form of 'objectivity,'" I suggested.

"Does it serve those boys experiencing discriminatory discipline? Or does it primarily protect the institutions implementing these practices from direct criticism?"

The question lingered between us as recognition dawned on her face.

The False Equation: Methodological Rigor and Moral Neutrality

Statistical training correctly emphasizes methodological rigor to minimize measurement bias. However, this valuable methodological principle has been misapplied as a demand for moral neutrality in how we interpret and present findings. These are fundamentally different concepts that serve different purposes.

Consider a practical example: A housing study employs paired testing to evaluate rental application responses. The researcher creates identical rental applications, varying only the applicant names to suggest different racial identities. The results show applications with traditionally Black-sounding names receive 50% fewer callbacks than identical applications with typically white-sounding names. These findings are statistically significant across multiple housing markets.

Under conventional research norms, the findings might appear in this disconnected manner: "Applications with African American-associated names received statistically significant fewer responses (p < .001) compared to identical applications with European American-associated names." The discussion might acknowledge "potential implications for housing access" without directly naming the discrimination revealed by the data.

This restrained approach serves no one except perhaps the researcher seeking to avoid controversy. It certainly doesn't serve the people facing systematic housing discrimination. It doesn't advance our understanding of how housing inequity operates. Most importantly, it fails to honor what the data demonstrates: clear evidence of racial discrimination that affects real people's lives.

During our Denver discussion, we explored how research with human participants establishes reciprocal obligations. When people share personal experiences, struggles, and vulnerabilities with researchers, they aren't volunteering merely to become anonymized data points. They participate because they hope their contributions might lead to meaningful change. This creates an ethical responsibility that extends beyond methodological correctness to include accurate representation of what the data reveals about injustice.

The Strategic Advantage of Positioned Knowledge

Advocating for our research participants doesn't require sacrificing methodological excellence. Rather, these approaches reinforce each other. Much like skilled attorneys who build compelling cases through meticulous investigation and evidence gathering, effective researchers employ rigorous methods while maintaining clear purpose.

I witnessed this synergy while mentoring a doctoral student who was studying college persistence barriers among first-generation students. As a first-generation college graduate herself, she worried her personal experiences would "contaminate" her research with bias.

"Your firsthand knowledge of these challenges isn't a limitation to overcome," I explained during our meetings. "It's an analytical asset that provides contextual understanding others might miss. The goal isn't to pretend you have no perspective—it's to acknowledge your position transparently while applying rigorous methodology."

Following this approach, she produced research that satisfied traditional methodological standards while offering unusually nuanced insights. Where previous studies had merely documented higher dropout rates among first-generation students facing administrative barriers, her analysis revealed how these bureaucratic obstacles triggered familiar feelings of institutional exclusion and reinforced perceptions that higher education wasn't designed for students like them.

Her findings resonated powerfully with participants precisely because she recognized patterns that might have seemed disconnected to researchers without her experiential knowledge. Her personal understanding didn't compromise her research quality—it fundamentally enhanced both her methodological choices and interpretive framework.

Navigating Political Headwinds Through Principled Advocacy

After our formal AERA session concluded, several of us continued the conversation with the doctoral graduate who had raised the initial question. Her concern reflected a broader challenge facing education researchers today: conducting and presenting work on equity in an increasingly polarized environment where even terms like "diversity" and "inclusion" have become political flashpoints.

This current climate creates tangible professional risks, particularly for early-career scholars. Research addressing racial disparities, gender equity, or LGBTQ+ student experiences may face heightened scrutiny, funding challenges, or public criticism despite methodological excellence and empirical validity. These pressures can lead researchers to dilute their findings or obscure clear implications to avoid controversy.

I suggested an alternative approach:

"Rather than retreating from advocacy in difficult moments, this is precisely when we must embrace our representative responsibilities more fully. When an attorney faces a skeptical judge, they don't abandon zealous representation—they prepare more thoroughly and argue more precisely."

"What you're undertaking," I continued, "isn't merely data analysis—it's bearing witness to lived experiences that might otherwise remain unacknowledged. Your participants entrusted you with their stories because they believed you would represent them accurately and completely. That trust carries significant ethical obligations."

This perspective offers researchers a clear ethical compass during politically challenging times: our primary allegiance must be to rigorous methods and faithful representation of our participants' realities, regardless of whether those realities align with current political preferences.

A Framework for Ethical Representation in Research

The false dichotomy between methodological rigor and ethical advocacy has constrained our work for too long. Effective research requires both elements working in concert: meticulous methods combined with clear commitment to representing participants ethically and completely.

Implementing this approach requires specific practices:

1. First, researchers must practice positional transparency by acknowledging their relationship to the communities they study. This doesn't undermine credibility—it establishes authentic context for interpretation.
2. Second, methodological excellence remains non-negotiable. Advocacy without empirical foundation lacks persuasive power. Precise methods, careful analysis, and appropriate statistical techniques are essential components of effective representation.
3. Third, findings must be contextualized within broader historical and systemic patterns. Isolated data points gain meaning when properly situated within larger societal frameworks that shape participants' experiences.
4. Fourth, researchers should clearly articulate the practical implications of their findings rather than leaving readers to infer applications or recommendations. If data reveals inequitable outcomes, name them directly.
5. Finally, participant voices should be centered throughout the research process—not merely extracted for academic purposes but amplified through thoughtful representation that maintains their dignity and agency.

Our conversation in Denver crystallized something fundamental about research purpose. At its core, research is relational work that establishes ethical obligations between researchers and participants. When people share their experiences, they entrust us with representing those realities accurately and completely.

To early-career scholars navigating today's complex research environment: Your participants deserve the same quality of representation you would want if someone were documenting your experiences. Apply rigorous methods, certainly—but pair that rigor with equally rigorous commitment to representing their stories with clarity and conviction.

The traditional veneer of detached objectivity has primarily served institutional interests rather than the communities most needing recognition. The alternative is not methodological compromise but a more honest approach: principled advocacy grounded in empirical excellence.

In this contested moment when empirical evidence itself faces political challenges, who will speak the documented truths our research reveals if not the researchers who discover them? The responsibility falls to us to represent our participants faithfully—not despite academic traditions, but because the highest purpose of those traditions has always been to advance human understanding and well-being.

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Dr. Ivory A. Toldson is a professor of counseling psychology at Howard University, editor-in-chief of The Journal of Negro Education, and chief of research for Concentric Educational Solutions. Author of the Brill bestseller "No BS (Bad Stats): Black People Need People Who Believe in Black People Enough Not to Believe Every Bad Thing They Hear about Black People," his work critically examines how research methodology and statistical representation impact communities of color. Previously appointed by President Obama as executive director of the White House Initiative on HBCUs, Dr. Toldson has challenged traditional research paradigms throughout his career, advocating for methodological approaches that center the experiences of marginalized communities while maintaining scholarly rigor. His expertise in leveraging data to promote equity informs his work with school districts nationwide.