Sọrọ-sókè: Unveiling the theatrics of justice and resistance in Nigeria's #EndSARS movement
Bibliographic record
Abstract
The Sọ̀rọ̀-sókè movement, which emerged from the #EndSARS protests of 2020, marks a crucial moment in Nigeria’s resistance against systemic injustice. The Yoruba phrase “Sọ̀rọ̀-sókè” meaning “Speak Up” "or “Speak Louder,” became a unifying anthem, capturing the collective outcry against police brutality, particularly the abuses of the Special Anti-Robbery Squad (SARS) of the Nigeria Police Force. Employing Digital Artivism as its theoretical framework, this thesis explores the blending of art and activism within the Sọ̀rọ̀-sókè movement. It analyzes how creative expressions and performative elements served as powerful tools for mobilization, resistance, and reclaiming narratives. Grounded in Practice-Based Research (PBR), the study integrates the digital archive, artivism.ca, which documents #EndSARS protest artworks, with this written art-critical analysis that contextualizes their cultural and political significance. Utilizing Feldman’s Model of Art Criticism and Qualitative Content Analysis as methodological frameworks, the research examines the theatrical and performative elements of selected protest art. It investigates how these creative strategies amplified the movement’s message, challenged government narratives and united diverse populaces in the fight for justice. This study contributes to broader discourses on the intersection of art and social justice, positioning the Sọ̀rọ̀-sókè movement as a seminal example of how artivism can disrupt entrenched systems of oppression and inspire collective action. By critiquing and contextualizing protest artworks, this thesis highlights the enduring impact of the Sọ̀rọ̀-sókè movement on Nigeria’s sociopolitical landscape and its implications for global struggles against systemic violence and inequality. Additionally, it sheds light on the theatrical nature of activism and its transformative potential for societal change. Keywords: social movement; protest art; policing; digital artivism; online activism; digital archive; youth-led movements; artistic resistance
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.012 | 0.021 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".