Freedom Dreams Occur at the University: A Comparative Study of Black Student Activism in the United States and South Africa
Bibliographic record
Abstract
In 2015, Black student movements emerged in the United States and South Africa, respectively: Black Liberation Collective and Rhodes Must Fall/Fees Must Fall. Existing research is taking notice of students’ frustrations with universities, by exploring their protests, which are centered on transforming higher education and decreasing tuition fees. The literature on student movements overlooks the role of identity politics in mass student mobilization. However, social media is exposing a trend of Black student activism in the United States, Canada, Latin America, Europe, and Africa. Yet, academic accounts and articles focus solely on Black student movements within the confines of their nation-states or institutions. By conducting a comparative study, this research explores the political, social, and economic factors causing the resurgence of cross-institutional Black student activism. I combine my comparative study with content analysis and auto-ethnography to insert lived experiences of engaging in student activism at Macalester College and direct action alongside Black Lives Matter Minneapolis, to add my own subjectivity into my research. In this study, I found Black students in the United States and South Africa are discontent with the broken promises of neoliberal post-racial democracy, are frustrated with the colonial and racist culture embedded in universities, and so seek to repurpose universities while simultaneously fighting for racial liberation. Ultimately, I encourage Black activists to form transnational networks to aid each other in redressing contemporary Black struggles.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.020 | 0.009 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".