Bibliographic record
Abstract
African Documentary Cinema investigates the inception and trajectory of contemporary documentary filmmaking in sub-Saharan African countries and their diasporas. The book challenges critical paradigms that have long prevailed in African film criticism, shedding light on the diverse discourses and evolving aesthetic trends present within documentary films. Situating his analysis within the context of the significant transformation of the African film industry, the author focuses on the development, diversity, and shifting dynamics that have impacted contemporary documentary cinema. Examining the historical, political, sociological, economic, and cultural factors that have facilitated the rise of documentary films—especially those created by female documentarians—the book assesses the emergence of documentary filmmakers spanning different generations. Their training, practices, and innovative perspectives on social, political, and environmental issues ultimately give rise to new frameworks for understanding the bio-documentary genre, issues of gender discrimination, LGBTQIA+ identities, environmental trauma, genocide, and memory on the African continent. This ground-breaking study offers new insight into a rapidly expanding topic and will appeal to students and scholars in the fields of film studies, documentary film, media industry studies, African studies, French, postcolonial studies, politics, and cultural studies.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.039 | 0.004 |
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".