Sport and Black/African-Palestinian transnational solidarity: a conversation
Bibliographic record
Abstract
This paper is an edited transcript of an online panel that took place February 11, 2025, exploring the historical and contemporary forms of Black/African solidarity with the Palestinian liberation movement within sport. Foregrounding the long tradition of leveraging sport within various anti-racist, anti-colonial, and anti-imperialist movements worldwide, this conversation emphasizes the urgency of developing sustained and renewed strategies of resistance. First, we outline Black-Palestinian Transnational Solidarity (BPTS) as a historical movement sustained by shared anti-imperialist principles. For decades, radical and revolutionary Black and African peoples have recognized Zionism as an extension of the racialized Western imperial project that significantly impacts Africans through colonization and economic exploitation. Second, we share the edited transcript featuring Joezer Antoine, Sean Jacobs, and Munene Mwaniki, who share their insights on a range of themes surrounding BPTS and sport. Key themes include: (1) the pivotal role of Africa in BPTS; (2) the inherent risk of anti-imperialist activism and the critical role of education; and (3) the need to challenge the (neo)liberal co-optation and pacification of liberation struggles. To resist and neutralize Western Civilization's deadly violence, we must build coordinated movements, deepen our understanding of revolutionary theory, and remain committed to the inherently destabilizing global anti-imperialist struggle.
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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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.028 | 0.018 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.003 | 0.007 |
| 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".