USASBE 2016_Presentation Slides

Editor's Notes

• #3: Wheadon: *Male participants often described themselves as “entrepreneurs” *No female participants used that term to identify themselves or their business activities at any point that season Logan: *Majority of participants did not think of themselves as entrepreneurs *Many did not like the label “entrepreneur” Dohrman: *Female business owners intentionally avoided using the term “entrepreneur” to describe themselves or their work *Also attempted to prevent their companies from being recognized as one created by a female
• #5: The reluctance of women to call themselves entrepreneurs may not seem noteworthy in isolation, but when examined within the context of other disciplinary gender gaps, it is an important key to understanding how and why men and women often identify differently with the concept of entrepreneurship
• #7: How we TALK about entrepreneurship is both a symptom and a catalyst for the larger issues that are simultaneously producing and reproducing gender gaps such as these in entrepreneurship
• #8: In a cultural context, the recognition earned by adhering to a certain set of standards or expectations over time is often exchanged as a sort of symbolic capital in return for various types of legitimacy (Bourdieu, 1993). This proves problematic in entrepreneurship, where gender can influence whether or not one identifies oneself as an entrepreneur or is thought of as an entrepreneur by others, impacting the amount of symbolic capital, legitimacy, and resources available to them (Bury, 2011; Goss, Jones, Betta, & Latham, 2011; Rindova, Barry, & Ketchen Jr., 2009; Zott & Nguyen Huy, 2006).
• #10: This research used a mixed-methods approach rooted in sociolinguistics to examine the influences of context, culture, society and expectation on the way language is used, as well as the reciprocal effects of language and word usage on individual and social constructions of perception and meaning
• #11: Looking at gendered alternative terms used to identify females in place of the word “entrepreneur.” The study investigated Question 1 from both an individual and a collective/social perspective: a) self-categorization (i.e., what do female entrepreneurs call themselves?), and b) categorization by others (what are they being called by society?). Especially paying attention to ASSIGNATION vs. ADOPTION as indicators of power differentials and the possibility for agentic action commonly examined in sociolinguistic inquiries.
• #12: While Question 1 examined what labels are being attached to female entrepreneurs, Question 2 focused on better understanding how and why these alternative gender labels for entrepreneurs are being linguistically produced.
• #13: Corpus linguistics frequency analysis of 39 databases (Proquest as corpora)
• #14: This study expands the existing research by conducting a textual analysis of the discourse in the data sample, which included 15 episodes comprising the first season of Shark Tank, originally airing between August 2009 and January 2010. The 15 episodes depicted a total of 68 presentations (or “pitches”) by 90 entrepreneurs, as well as an assortment of short “backstories” for 45 of the participants allowing them to expand on their backgrounds. Narrowing the content of the previous study to include only portions of the show depicting female entrepreneurs, Season 1 featured a total of 33 female entrepreneurs who introduced themselves, described their companies, and/or pitched new business ideas. Twenty-three of these women received additional air time to further introduce them to the audience during a backstory. Recordings of the female segments from each episode were transcribed and then coded to compile quantitative 
descriptions of the content ** GENDER-Related and RELATIONAL terms
• #15: To provide a larger context for the research, Proquest databases were used to access portrayals of and discourse surrounding female entrepreneurs in the contemporary media, and a corpus linguistics analysis was performed on the resulting data.
• #16: Used a different corpus for comparison, specifically the Corpus of Contemporary American English (COCA). The COCA analysis examined 450 million words of text in the American dialect that include 20 million words each year from 1990-2012 equally selected from spoken, fiction, popular magazines, newspapers, and academic texts. This analysis focused specifically on the collocation (or appearance together more frequently than would happen by chance) of the gendered words male/man/men and female/woman/women within one word before or after the words “entrepreneur” and “entrepreneurs.” Mutual Information score is a measure of how tightly linked two words are. This takes into account the overall frequency of collocates. MI=3.0 is usually considered high. “Entrepreneur” marked for gender almost 8.5 x more often when referring to females than males (8.3). The results of this study indicate the presence of a moderate collocation frequency (both positive and negative, depending on the gender) between the use of gendered terms to mark the word “entrepreneur.” ** Signifies “entrepreneur” as a MARKED term