Bibliographic record
Abstract
Distributed by Green Planet Films, PO Box 247, Corte Madera, CA 94976-0247; 415-377-5471Produced by Inanc Tekgüc and Eda Elif TibetDirected by Inanc Tekgüc and Eda Elif Tibet2022, Streaming, 77 mins AÏT ATTA: Nomads of the High Atlas, directed by Inanc Tekgüc and Eda Elif Tibet is a visually stunning journey to the rugged landscapes of Morocco's High Atlas Mountains. This film follows the remarkable journey of the Ben Youssef family, a nomadic tribe navigating the challenges of preserving their ancient way of life in the face of modernization and environmental change. The annual migration the Ben Youssef family makes from the deserts of Nkob to the pastures of Igourdane is not an easy one. They make the journey on foot. They struggle to find ample food and water on their 93-mile journey. They contend with unforgiving terrain and unpredictable weather. They are separated from their children who live with family members so they can attend school. Yet amidst these hardships, the documentary captures moments of resilience as the family cares for their livestock and prepares traditional meals. Watching the Ben Youseff family on their trek is a rare glimpse into an ancient lifestyle that we are at risk of losing. This nomadic community continues their yearly quest to reach the agdal (a communal land management system) where they exercise their ancestral right of access despite challenges from settled villagers. AÏT ATTA presents a candid portrayal of a disappearing way of life. With its personal narrative and imagery, the film serves as a powerful reminder of just how important it is to preserve cultural heritage in an ever-changing world. Awards:Oniros Film Awards, December 2020 Best Documentary; Golden Sun Award Best Documentary Film Suncine Barcelona 2021, QIIFF Quetzalcoatl Indigenous Film Festival Oaxaca Mexico 2021
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 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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.920 | 0.816 |
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".