This thesis seeks to understand the how texts are constructed to forward feminist communicative objectives through a case study of Dr. Karen Kelsky’s "A Crowdsourced Survey of Sexual Harassment in the Academy." In this research, sexual harassment is understood as an act of power, sexual in nature, enacted by faculty or staff (employed or contracted in different capacities) in their relations with other faculty or staff, who are often lower ranking. By adopting invitational rhetoric as a theoretical framework, this thesis examines the way Dr. Karen Kelsky's crowdsourced survey creates the space to articulate and elevate often suppressed personal testimony regarding sexual harassment. By welcoming, and then displaying, narratives that have been deliberately silenced over the course of history, Kelsky’s spreadsheet showcases a collective consciousness surrounding sexual harassment in academia. The current scholarship surrounding feminist communicative praxis highlights the importance of the written personal narrative as meaning-making and as a reflective practice, especially through the medium of journaling. However, this research examines how texts can employ personal testimony to co-create meaning as a mode of resistance. In particular, Kelsky’s artifacts create a space that privileges and displays situated knowledge about sexual harassment that has been otherwise obfuscated. By conducting a feminist rhetorical analysis, this thesis argues that Kelsky's artifacts perform invitational rhetoric that mediates situated knowledge surrounding sexual harassment in the academic workplace. Reflection and dialogue shape the nature of storytelling as evoked by the survey, which are approached by this thesis as feminist communicative praxes that are activated throughout engagement with the artifacts.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd-7068 |
| Date | 01 January 2018 |
| Creators | Molko, Rachel |
| Publisher | STARS |
| Source Sets | University of Central Florida |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Electronic Theses and Dissertations |
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