Excluded from privilege? Black American fraternity men’s negotiations of hegemonic masculinity
Bibliographic record
Abstract
In the United States in 2015, race and masculinity are at crucial sociopolitical crossroads – particularly as individuals and communities attempt to navigate the complicated experiences Black American males must face under the backdrop of police brutality, violence, and racism (Brunson, 2007; Crenshaw, Gotanda, Peller, & Thomas, 1995). In a time where Facebook and twitter hashtags have to remind us that #blacklivesmatter, we must support space for Black men to tell their own stories about how they navigate masculinity within cultural discourses that demonize, problematize, and construct what it means to be a Black man in America. In particular, this manuscript will focus on Black fraternity men’s self-perceived understandings of masculinity as developed within Black fraternity spaces with/in American culture. These self-perceived understandings highlight the complex state of raced masculinities caught within and pushing against hegemonic expectations of gender, religiosity, heteronormativity, and ethics of care within current American contexts.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.028 | 0.018 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".