This research demonstrates the value autoethnography has to “debunk” the dominant narrative of being an underrepresented first-generation college student in higher education. Motivation for this study arose because four of my colleagues and I experienced inequity with our autoethnographies at the 2021 online Student Research Symposium (SRS). Judges came unprepared and uncredited our experiences, sending a message that autoethnography is not serious research. Autoethnography’s a process and a product of researching and writing that seeks to systematically describe and analyze personal experiences to understand cultural experiences (Ellis et al., 2011). This approach challenges canonical ways of doing research and representing others as a political, socially-just, and socially-conscious act in a collective counterstory that “challenge[s], displace[s], or mock[s]... pernicious narratives and beliefs” of the dominant culture (Delgado and Stefanic, 2012, p. 43) I start as an undergraduate autoethnographic presenter in SRS 2021, turned activist challenging fairness from San Diego State University’s (SDSU) practices assessing student research. Then, I’m a participant in 2019’s Health Careers Opportunity Program (HCOP) summer seminar, first learning about qualitative research. Lastly, as an independent undergraduate scholar, I have chosen a representational research analysis approach (Creswell & Poth, 2018, p.199) to identify the principal themes across 13 of 15 undergraduate autoethnographies including my own from the 2019 inaugural summer seminar of SDSU’s HCOP. For this exploratory study, I analyzed seven of 13 selected authentic autoethnographies with the following content analysis: 1) Reading and memoing emergent ideas. 2) Holistic classifying codes into themes. 3) The unit of analysis was the paragraph as delineated by formatting conventions. Word count was calculated for each paragraph and a statistical formula was used to render the word count of the paragraphs roughly equivalent so there were no very large or very small paragraphs in the clean data set. 4) Hand coding preceded the use of NVivo to identify themes that were common across all autoethnographies. 5) Using the results of NVivo, representing and visualizing the data to form a meta-counterstory that has potential for generalizability to other institutions and programs similar to SDSU and HCOP.