Portrayal of animal factory farming practices in young children’s books with reference to the German context
Bibliographic record
Abstract
Traditional small-scale farms are progressively being replaced by large-scale factory farms. Their single purpose is to produce inexpensive animal products while maximizing efficiency, productivity, and profit, and reducing production costs, at the expense of animal welfare and environmental destruction. Practices associated with intensive animal farming have been criticized by public health authorities and animal welfare advocates (e.g. narrow gestation crates for pigs, mother-calf separation immediately after birth, overcrowded stables using slatted flooring, and the extensive use of prophylactically administered antibiotics). Polls indicate that the public is often unaware of the extent and implications of factory farming practices and children in particular are often not taught realistically about the farm sources of their food and the conditions in which animals are raised. The present study sought to explore the extent to which the aforementioned farming practices were depicted in a convenience sample of German children’s books (n = 38). Common practices such as mother-calf separation after birth and cattle dehorning were shown in less than 25% and 30% of books, respectively. Cattle/pig tail docking and battery cages for hens appeared in 0% and 8% of books, respectively. Procedures such as animal branding or debeaking were not shown. Farms were depicted in bucolic settings yet with minimal depictions of animals being outdoors in natural light. Our analysis supports that common animal farming practices associated with animal exploitation are not portrayed realistically in German children’s books. Barring children from the realities of factory farming indirectly reinforces the acceptability of these unnecessary unethical violent practices.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".