Bibliographic record
Abstract
When the popular video film debuted in Nigeria in the late 80s, filmmakers and critics sympathetic to celluloid perceived it as a fad that would soon extinguish. The cinematic culture, bequeathed by British colonialism, was thought to have generated a discerning film audience that would shun the video medium. This was not to be. The video film has grown from a few productions in the late 80s to more than 1000 features per year. Unlike celluloid before it, video is truly a popular medium. The same social and economic downturn that necessitated its rise as a direct alternative to celluloid is what ratifies video as a medium for dramatizing popular concerns. It is video's ability to enact and circulate – outside of the state's ability to control – that makes it fruitful for studying decolonization. More, the Nigerian popular videos have been able to break national boundaries and acquire a broader African audience, suggesting immediately that there is a commonality in the pain of popular experience across Africa's post-colonies. This paper outlines the categories of spaces for seeing video films – as sites for contesting self and other identities among popular masses – from Lagos to Douala.
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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 | 0.001 | 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 | 0.010 | 0.009 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".