Beyond Hollywood Formulas: Evolvıng Indigenous Yoruba Film Aesthetics
Bibliographic record
Abstract
Home video scholarship is an emerging aspect of theatre studies in Nigeria. While previous studies have been merely critical of Nigerian film practitioners’ inability to evolve an indigenous form, they have failed in prescribing necessary strategies for achieving this. This study, therefore, fills this gap by proposing devices for evolving an indigenous meta-language for the Nigerian film industry. It concludes, amongst others, that Nigerian film industry should evolve an indigenous film language through a fusion of traditional story telling forms and conventional film codes. Key words : Film; Indigenization; Yoruba video film; Aesthetics Resume: La bourse du Home video est un aspect emergent des etudes theatrales au Nigeria. Les etudes precedentes ont ete simplement des critiques de l'incapacite des praticiens du cinema nigerian d’elaborer une forme indigene, et elles ont echoue dans la prescription des strategies necessaires pour atteindre cet objectif. Cette etude, par contre, comble cette lacune en proposant des dispositifs pour une evolution de metalangage indigene pour l'industrie cinematographique nigerienne. Il conclut, entre autres, que l'industrie cinematographique nigerienne devrait trouver un langage cinematographique autochtone via une fusion entre les formes de recit d'histoire traditionnellse et des codes cinematographiques conventionnels. Mots-cles: Film; Indigenisation; Film Video En Yoruba; Esthetiques
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".