My research shifted multiple times throughout third and fourth quarter in ways I hadn't anticipated. However, this research process has taught me that those fluctuations are necessary. Through my results, and the different pathways my research took, I was able to draw new conclusions and gain a better understanding of my topic, limitations, and implications. Sharing my research with my community was the most rewarding part of this entire journey. 

My research shifted to focus on measuring average model measurements from an internal and external perspective. As argued by communications professor Araceli Bachner, comparisons using these two perspectives is vital in evaluating the perception of true change. I compared the 2024 VS show to the 2018 VS Show, the last runway before its cancellation, and to the Savage X Fenty Vol 4 Show, it's most recent runway which occurred in 2022.  I used Savage X Fenty as it’s a prevalent and arguably top competitor referenced in Odell and Tyrnauer’s research that has also been evaluated by Vogue magazine. My comparison to Fenty was used to be generalized towards the rise of more inclusive lingerie brands. 

I created a table for each measurement category, waist size for example, and placed model data into their respective 2018 or 2024 row. 

Stapplet, a well-known data-analysis platform, ran an analysis on my data and produced two dot plots for comparison. The visuals and data table for 2024 vs 2018 waist measurements are displayed above next to the dot plots for all measurements in the internal comparison. You can observe how 2024 has more outliers and variability, accounting for a wider range of model sizes. Since those outliers are consistently right-leaning, they represent larger measurements. I saw this trend throughout all measurements in the internal comparison. 

For my external perspective, testing whether VS has caught up to competitors, I conducted the same analysis, this time with comparing Fenty and VS. All other elements of analysis remained the same however with Fenty being the dot plot on top and VS on bottom. As expected, across all measurements Fenty had more variability and outliers as seen in the dot plots above. 

I initially was focusing on visualizing my data through bar graphs. I later realized I needed to focus on providing statistical significance to my data. I worked with my AP Statistics teacher to conduct a two sample t-test for a difference between means. I was looking for convincing evidence that within each category the 2024 average measurement would be greater than 2018 (μ₁ - μ₂ > 0).  μ₁ represents 2024, for example average 2024 waist size, while μ₂ represents the 2018 equivalent. This is because 2024 having larger averages translates to having increased representation. I want to point out that for height, my hypothesis was μ₁ - μ₂ < 0 because typical model standards are to be tall, thus increased representation would look like the inclusion of shorter models, theoretically making 2024 average height less than 2018. For my external comparison, μ₁ represents Fenty and μ₂ represents VS to measure whether Fenty had more representation.  

Conducting a 2 sample t-test produces a p-value, a value I used to determine whether there was convincing evidence for my research hypothesis. In my study, I used the most common significance level used in statistics: 0.05. Thus, any p-value less than 0.05 accounted for there being significant evidence towards there being increased representation in 2024, for the internal comparison, or Fenty, for the external comparison. For instance, in my internal comparison waist size example, Stapplet calculated a p-value of 0.043. Since this value is less than the significance level, the difference between 2024 and 2018 waist sizes was significant, meaning 2024 had increased representation in waist measurements. 

Concerning the internal comparison, after calculating p-values for each measurement, I found a significant difference in height, waist, and dress measurements. However, in bust and hip measurements, there was not convincing evidence for increasd representation. Thus, my hypothesis from the internal perspective is partially supported with the different in 3 out of 5 categories being significant. 

For my external perspective, across all categories, the calculated p-values represented significant differences between Fenty and VS measurements. This gave me convincing evidence that Fenty consistently had more representation, supporting my hypothesis entirely from the external perspective.

A major limitation I faced throughout my research was model measurements not being available online. The Fashion Model Directory lacked profiles for several models, so I used other sources like model agency databases. While this deviation from my methodology was not ideal, I still trust its accuracy as these agencies represent models in their careers. 

I struggled the most with finding models' dress sizes, with many databases lacking that measurement. Thus, those averages do not represent all models dress sizes, however the majority are accounted for. 

These limitations had the largest impact on my Fenty data collection. 23 models did not have profiles on the Fashion Model Directory and 14 models did not have measurements anywhere online. 

However, through this limitation, I noticed the majority of those models differed more from the stereotypical model look. Thus, I’m assuming the inclusion of this missing information would have increased the Fenty's average measurements, creating a larger deviation from VS and further supporting my hypothesis. This limitation also made me realize that many of Fenty’s models weren’t actually models. They didn’t have model profiles as they weren’t prominent figures in the modeling industry, rather they were celebrities and influencers. VS, on the other hand, consistently employed models with 20 returning from previous VS shows, 12 of which were retired Angels. An argument can be made that those returning Angels drove a large audience back to the show. However, as reported in the Aesthetic Surgery Journal, no VS Angel or runway model prior to 2024 was considered plus size or even mid size. Thus, my results pose the question: did VS bringing back these veteran models limit their increase in body diversity? My research provides convincing evidence that it was limiting. 

Returning to my research question, my data allows for different interpretations if VS's changes in body diversity were enough. This depends on whether you prioritize internal or external comparisons.

Following the 2024 runway, Forbes magazine argued “Under business duress, when brands treat diversity as an obligation rather than a commitment, they fail to make a lasting impact”.

Conversely, in a CNN article, celebrity stylist Law Roach commented positively on the show, saying “I think it is a work in progress. It is a good start."

My data, alongside the conversations begun by a plethora of prominent fashion magazines, provides researchers with a better understanding that representation can be a difficult term to coin, let alone truly achieve. I implore future studies to conduct this same research on other brands to help the industry have a better idea of what true representation looks like, solidifying its meaning. 

I've loved the whole investigation and project creation journey throughout this class and would love to continue my studies of the modeling industry, hopefully with the help of industry mentors and my college professors. I am also interested in looking into publishing my work as a peer-reviewed study and am excited to explore that process this summer. I will be attending University of Colorado Boulder (CU) in their Leeds School of Business. I am really looking forward to being a part of Leeds Scholars and the Presidential Leadership Class at CU. This research process has taught me invaluable lessons that I am so grateful to bring into college with me. I've learned the importance of committing to an idea, asking for help when needed, being adaptable, and working ahead to allow room for mistakes. I see these values helping me in pursuing future projects, research, and goals by being able to accept setbacks, utilize any and all resources, and be passionate about the process and its ups and downs. The academic paper portion of this class was an enlightening experience in writing a professional-grade research paper that will certainly be a prevalent aspect in my future business education. The presentation portion of this class showed me how to properly prepare for giving a pitch, briefing, or speech with confidence. Similarly, the oral defense portion of this class showed me that presenting is your time to show off what you know. Presenting and being proud of your work is an essential component to the business industry. This research class has without-a-doubt strengthened my skills to move forward in my education with confidence and diligence. Reflecting on my personal growth through this class, I've learned to let things go, such as my hyper fixation on perfection. In fact, it's the "unperfect" elements of your research that may lead to new discoveries and more opportunities for future studies. 

I want to thank Mrs. Dobos and Mr. McBride for their devoted support throughout this entire research process. They always welcome us into class with a cheery "Good Morning" which set each day off right. They've trusted us and treated us as adults as we navigated the trials and tribulations of time management, discovering our weaknesses, and celebrating out accomplishments. I also want to thank Mr. Burridge, my AP Statistics teacher, who helped me gain a solid understanding of the statistical analysis necessary for this project. I'm extremely grateful for the family, friends, and RC staff who supported me in presenting my final research at both the College Board Exam and Research Symposium: Tara Broyd, Pete Solano, Zoe Solano, Mrs. Kubina, Ms. Lamb, Mr. Kroll, Mr. Clark, Mr. Abner, Mrs. Burridge, Riley Kerstiens, Mrs. Kerstiens, Morgan Dodd, Lauryn Goode, Aspen Heppe, Bree Judd, Aspyn Motarjeme, and Cleo Melville. For future researchers, I advise you to seek out strong support systems like my own as they make the research process all the more worthwhile and impactful. Thank you all.