The Art of Social Justice Research: Creating and Validating Instruments for Workplace Bullying Research

This book is designed for social justice minded scholars who might have an original love for qualitative research, language, interviews, and coding. As I tell my doctoral students, qualitative methods are not harder than quantitative methods; the converse is true. Quantitative methods are not harder than qualitative. They are different and bring different issues, all of which can be transcended with enough grit and determination. To give the reader context, I majored in English Literature and Africana Studies at a time that “Black Studies” was not wholly embraced. It was considered a “nice” second major. Since that time, starting with Dr. Molefi Asante’s inaugural doctoral program in Black Studies at Temple University, several colleges and universities have also embraced the value of ethnic studies doctoral programs [Karenga, Journal of Black Studies, 49(6), 576–603 (2018)], Cornell University, Penn State University, University of Texas-Austin, and Yale University, to name a few. Since the 2022AERA conference in San Diego, I found myself wondering why more BiPOC scholars did not embrace statistics. I asked my mentors and colleagues, who have noticed the same phenomena. It left me asking, where are the Blacks in Stats? Then I thought of what we know about student development along racial, gendered, and socio-economic lines. Women are typically ostracized in the STEM fields and find such environments uncomfortable. When I reflect on my own math history, I originally loved algebra. I had a wonderful teacher who crisscrossed the building in her red clogs and blonde hair. She was accessible to boys and girls, leaving all of us liking math. Yet my math journey wavered when I had a male teacher for calculus. I found him to be dismissive and belittling. I did not like the class and focused more on subjects that brought greater rewards, such as being accepted by the teacher. I grappled again with math and statistics in my doctoral program and found that the research questions I had were not qualitative. My research pursued predictive models such as “what services truly serve student athlete graduation rates” [Hollis, Equal opportunity for student-athletes: Factors influencing student-athlete graduation rates in higher education. Boston University (1998)]. I went from being immersed in the slave narratives, Langston Hughes, Zora Neale Hurston, and Richard Wright from my Bachelor’s and Master’s programs straight to higher end thinking in multiple regressions. Like many doctoral students, I sought a statistics tutor and learned to establish the study, create the survey, set up the database, and run the analysis in StatView. My dissertation led to a multiple regression study published in one of the top higher education journals, Journal of College Student Retention [Hollis, Journal of College Student Retention: Research, Theory & Practice, 3(3), 265–284 (2001)]. After graduation, I then went on my merry way into administration, but still with a love for writing and research. During my administrative career, I had a great professional comrade in Dr. Earl Shaw, a renowned African American physicist at Rutgers-Newark. He was an African American gentleman who was raised in Mississippi and completed his doctorate at the University of California Berkeley; when he came to Rutgers-Newark, he brought a laser from Bell Labs. In his professional career in higher education, he discussed physics in a way that made so much sense to me. At the time, I was the director of the Learning Resource Center at Rutgers-Newark and knew that our students requested algebra tutoring more than tutoring on all other subjects combined. So I asked Dr. Shaw, “Why is it that our kids struggle with math?” His answer was an elegant one: “When you are studying Ralph Ellison or even about Western Europe, it isn’t foundational. You don’t need to know Chaucer to get to Shakespeare to get to Mary Shelley to get to Phyllis Wheatly. In STEM, one must master each foundational step. Also, it requires concentration. Sure, you can put your headphones on and read on the subway. Close it when you get to your stop, and then reopen it. ? You can’t do that. You must have quiet and be undisturbed. Let’s face it, our kids have so many distractions. If Mom is working a double, that student can’t ignore his three little siblings. If a high school student has a job, then commuting, then housework, then biochemistry? Not happenin’. So many of our kids are trapped in their socio-economic position that even the smartest don’t have extended and secure peace and quiet. So our kids struggle more in math and science. The approach to studying is different.” Dr. Shaw’s answer always stuck with me. In short, he was saying those who come from compromised socio-economic backgrounds don’t have that “room of their own” [Woolf, A room of one’s own and three guineas. OUP Oxford (2015)] to study and analyze the wonders of math. I find that my brother, who is currently a stellar engineer, had quiet time and space, but we were blessed with our own rooms and our own desks and quiet time for homework (whether we liked it or not). But even in our own sleepy western Pennsylvania town, many students did not have such consistently quiet study environments. I kept this in mind through another ten years in student services. When I switched my careers from administration to educational research, I still had predictive research questions, now about workplace bullying. For my first project, a colleague convinced me that with a researcher’s training I should be clear that CITI standards are always followed. I created the instrument, tested it, and analyzed the data. The survey led to Bully in the Ivory Tower (2012), which still is a major success and the bedrock of my consulting. I then turned my focus to a tenure-track position and continued my survey research. I say to the reader, remember, I am the English major, the one who loved Alice Walker and Gloria Naylor. My background embraced August Wilson, Ralph Wilson, and Nella Larson. Yet my questions led me to statistics. I read quite a bit and have taught Introduction to Quantitative Methods at a Research 2 Carnegie Classified institution for doctoral students. Even the prep for a statistics class is vastly different than a course relying on theoretical discussions. Ten years later and with tenure, I have conquered math anxiety and found that young girl in me who went to algebra in her own red clogs. I could find myself in the data, and I have created a stable and uninterrupted space to learn statistics techniques. Now I tell my students if I—Leah, the English major who hated balancing a checkbook—could do it, you can too. Students who come from backgrounds that did not allow for sustained quiet space often dance around stats, even choosing qualitative methods for research before they have designed the study. This strategy often emerges in an attempt to avoid statistics. Many students state that they want qualitative research because the math scares them, or they just don’t get it [Rodriguez, Journal of Hispanic Higher Education, 13(3), 191–205 (2014)]. If you’re one of those students who came out of the humanities or arts, and now you want to ask your own social justice questions, this book is for you. Perhaps you’re looking at a career in administration and policy development. Then statistics are needed to predict the best fiscal commitments. Even if one is not doing the calculations, one should be able to read the findings. From another vantage point, perhaps you are looking into social justice questions and want to develop your own data instead of searching for previously designed instruments and datasets. Regardless of the reason, this book discusses the research questions and hypotheses for eight instruments. There will be a discussion on different ways to tackle the question. Each instrument has also been validated and will have an accompanying Cronbach’s Alpha. New knowledge that leads to policy emerges from the numbers. The following chapters offer a pathway to minimize statistics anxiety for social justice solutions.