Contemporary eco-food films: The documentary tradition
Bibliographic record
Abstract
ABSTRACTThis article examines the central role food has played in documentary films as early as the Lumiere Brothers' 1895 view, Repas de bebe/Baby's Breakfast through the more recent eco-food films from United States, Canadian and European film-makers. Responding to non-fiction works of Michael Pollan, popular US documentaries such as Food, Inc. by Robert Kenner (2008) and King Corn by Aaron Woolf (2007) assert clear positions through their talking heads approach to exposition but draw on a limiting nostalgic view of food production. Austria's We Feed the World by Erwin Wagenhofer (2005) and multiple National Film Board of Canada documentaries, on the other hand, provide a depth of evaluation supported by multiple examples missing in both Food, Inc. and King Corn, yet weaken their arguments with an evenhanded approach to food ecology. Germany's Our Daily Bread by Nikolaus Geyrhalter (2005), however, comes closest to capturing the truth, offering fragmented observations that closely replicate the segmente...
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.008 | 0.009 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".