Bibliographic record
Abstract
This is an interview with Amina Weira, born in Niger in the second decade after the wave of African independences. It addresses her life and work as a filmmaker. Along with Sani Magori and Aicha Macky, she came to cinema in the dry years of the 2000s yet managed to position herself at the forefront of film production in Niger. For Weira, the documentary form, a much-maligned genre due to its association with mass political manipulation in the 1960s and 1970s, is the tool of choice for artistic creation. The introduction focuses on the images she crafts in La Colère dans le vent expounding a beauty only rivalled by the excruciating pains of men suffering untold diseases, due to their exposure to uranium pollution. The interview explores the making of Anger in the Wind (2016) and reveals an artist with a keen sense of justice, a woman given to moments of nostalgia yet revolted by the unending traumas suffered by the inhabitants of her native town: Arlit.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".