Internalized Oppression: Exploring the Nuanced Experiences of Gender and Sexuality in Historically Black Colleges and Universities
Bibliographic record
Abstract
In the American South at the turn of the twentieth century, quality education was scarce and legislative laws were put in place to ensure that African American individuals remained far away from Predominantly White Institutions (PWIs). As a result, Historically Black Colleges and Universities (HBCUs) became a catalyst for change in this “separate but equal” society. This article will explore the significance of HBCUs in elevating Black Americans throughout the twentieth century, while also assessing the conservative nature of the institutions and their inflexibility towards the various nuances of African American communities. While it is not particular to HBCUs, a tolerance of toxic masculinity and severe conservatism has resulted in starkly different Black experiences for cis-gendered heterosexual men, in contrast to cisgendered women and other members of the 2SLGBTQI+ community. By investigating various experiences within HBCUs, this article will explain the unifying and uplifting benefits for Black individuals in these institutions, as well as its many divisive components. My research will strive to analyze and properly convey the various nuanced experiences throughout HBCUs and assess the variety of factors that have led to these underrepresented interactions. This article will provide an understanding of how HBCUs have and continue to reflect American society but also demonstrate their role in various Black communities and their representation of non-dominant Black groups from the late nineteenth century to the present.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.020 | 0.026 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".