Bibliographic record
Abstract
Having fled the Liberian Civil War, renowned self-taught artist Johnson Weree is seeking asylum in the Netherlands where he lives undocumented and without a fixed address. Haunted by the horrors of his past, he draws bright-coloured otherworldly portraits, whilst longing for a brighter future. Weree is a short documentary film I have directed, produced, shot and edited in 2024. The film screened at film festivals in 2024-2025 and was subsequently released online in 2025. Awards Winner: Asolo Art Film Festival, 2025 - Best Short Art Documentary Winner: Newport Beach Film Festival, 2024 - Audience Award: Best Art, Architecture + Design short Winner: San Francisco Short Film Festival Presented by SF IndieFest, 2024 - Audience Award: Best Foreign Documentary Winner: African Diaspora Cinema Festival, 2024 - Best Short Documentary Winner: Shorts Mexico, 2024 - Honorable Mention Winner: The Fine Arts Film Festival, 2024 - Impact Award Winner: Sunderland Shorts Film Festival, 2024 - Honorable Mention Official selections Mammoth Lakes Film Festival Sidewalk Film Festival PÖFF Shorts Black Nights Film Festival Brooklyn Film Festival HollyShorts London Newport Beach Film Festival Sedona International Film Festival St. Louis International Film Festival Tacoma Film Festival Lunenburg Doc Fest Crested Butte Film Festival Eastern Oregon Film Festival San Francisco Short Film Festival Presented by SF IndieFest Sole Luna Doc Film Festival American Documentary Film Festival (AmDocs) McMinnville Short Film Festival Regina International Film Festival River Film Festival Sunderland Shorts Film Festival Fine Arts Film Festival Montreal International Festival of Films on Art - FIFA AVIFF le festival du film d’artiste African Diaspora Cinema Festival Snake Alley Festival of Film The Shortest Nights Newburyport Documentary Film Festival DokuBaku International Documentary Film Festival Shorts Mexic International Film Festival The Hague Pori Film Festival Yellowstone International Film Festival Rencontres du film d'art St Gaudens Girona Film Festival Festival internacional Signos da Noite Seattle Black Film Festival Asolo Art Film Festival Fargo Film Festival Positively Different Short Film Festival Gorinchem International Film Festival Dawson City International Short Film Festival Jim Thorpe Independent Film Festival
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.706 | 0.518 |
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".