Dirty South Feminism: The Girlies Got Somethin’ to Say Too! Southern Hip-Hop Women, Fighting Respectability, Talking Mess, and Twerking Up the Dirty South
Bibliographic record
Abstract
Within southern hip-hop, minimal credit has been given to the Black women who have curated sonic and performance narratives within the southern region. Many southern hip-hop scholars and journalists have centralized the accomplishments and masculinities of southern male rap performances. Here, dirty south feminism works to explore how agency, location, and Black women’s rap (lyrics and rhyme) and dance (twerking) performances in southern hip-hop are established under a contemporary hip-hop womanist framework. I critique the history of southern hip-hop culture by decentralizing male-dominated and hyper-masculine southern hip-hop identities. Second, I extend hip-hop feminist/womanist scholarship that includes tangible reflections of Black womanhood that emerge out of the South to see how these narratives reshape and re-inform representations of Black women and girls within southern hip-hop culture. I use dirty south feminism to include geographical understandings of southern Black women who have grown up in the South and been sexually shamed, objectified and pushed to the margins in southern hip-hop history. I seek to explore the following questions: How does the performance of Black women’s presence in hip-hop dance localize the South to help expand narratives within dirty south hip-hop? How can the “dirty south” as a geographical place within hip-hop be a guide to disrupt a conservative hip-hop South through a hip-hop womanist lens?
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.017 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".