Law and Black Agency in Memories of Abolition: Human Rights and Slavery Films
Bibliographic record
Abstract
Abolitionism holds a privileged place in human rights historiography. In scholarship and the wider social world, the abolition of slavery has frequently been celebrated as a foundational human rights moment. This celebratory discourse has also impinged on the medium of cinema: slavery films frequently propagate the view that abolition was a “gift” codified in law. In this reductionist discourse, law is configured as the guarantor of freedom and Black resistance to slavery is marginalised. By this strategy, the history of slavery is transfigured into a platform for the celebration of white moral indignation via attention to a canonised set of white patriarchs conceived of as philanthropic, moral crusaders, who are recognisably the forerunners of today’s white saviour “human rights heroes”. However, as we know, Black agency was also a decisive force in bringing Atlantic slavery to an end – most spectacularly in Haiti. Gillo Pontecorvo’s undervalued 1969 film Burn! offers an ideological critique of abolitionism and holds untapped potential for the radicalisation of human rights discourse today. Refusing the debilitating narrative that abolition was a legally encoded humanitarian gift, Burn! insists upon Black agency as a central historical force in the story of an as yet incomplete struggle for liberation.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.016 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 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".