Bibliographic record
Abstract
Distributed by epf media, 324 S. Beverly Drive, PMB 437, Beverly Hills, CA 90212; 310-839-1500Produced by Anneleen OphoffDirected by Anneleen Ophoff2024, Streaming, 29 mins Behind the Smokescreen is a fascinating short documentary about the deforestation and wildfire crisis in Bolivia. Behind the Smokescreen introduces the many factors of this issue, exploring the volunteer firefighters who risk their lives to preserve the vanishing rainforest, the farmers whose slash-and-burn practices lead to devastating fires, and the economic and political factors that contribute to widespread deforestation in Bolivia. Behind the Smokescreen briefly touches on how these issues affect Indigenous populations and highlights the sustainable farming practices used by some Indigenous farmers. The documentary is very informative and highlights an important issue that is not often on the radar of North Americans. The documentary has an informational narration and features the perspectives of multiple firefighters, environmentalists and park rangers. It only features one farmer, and the film stresses that many farmers are reluctant to talk to journalists. Contextual information about the political and economic factors are provided in voice over. Additionally, Behind the Smokescreen features gorgeous cinematography that captures affecting imagery of forest fires and makes for a moving and interesting documentary. With a run time of 29 minutes, Behind the Smokescreen is not able to delve particularly deeply into this multifaceted issue, but it does provide a captivating overview. The short run time is the only downside to this otherwise fantastic documentary. It leaves the viewer wanting to learn more about all aspects of this issue. Behind the Smokescreen is highly recommended, both for academic and general audiences. It would be most useful to Agriculture, Environmental Sciences or Latin American Studies. Though it touches on topics of interest to Indigenous Studies, there is not enough content to be useful in an academic context.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.627 | 0.215 |
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".