Protecting farm animal welfare during intensification: Farmer perceptions of economic and regulatory pressures
Bibliographic record
Abstract
Abstract Pig (Sus scrofa) production in Hungary provides a case study in how external pressures influence animal production, animal welfare and intensification. External pressures were explored in 24 in-depth, semi-structured interviews with Hungarian pig farmers operating either confinement or alternative systems. Confinement producers reported intense economic pressure because of a power imbalance with the large meat-processing companies that buy their animals. These companies, in the view of the farmers, can source internationally and largely dictate prices. When prices paid by the companies fall below the cost of production, farmers cannot respond by reducing production because of the long time-lags between breeding and marketing; and with their large investment in confinement buildings that are difficult to modify, farmers see little option except to reduce production costs further. Alternative farmers reported being more resilient to economic pressures because they sell into niche markets, use inexpensive technologies, and typically produce a diversity of agricultural products which buffer periods of low profit in any one commodity. The current regulatory system was seen as inadequate to protect animal welfare from economic pressure because it focuses on certain inputs rather than welfare outcomes, does not cover some important determinants of animal welfare, and does not accommodate certain realities of farming. Current subsidies were also seen as an inadequate remedy, and were viewed as inequitable because they are difficult for alternative producers to access. Consumer-choice options, while used by alternative producers, are not available in mainstream markets which demand uniform ‘commodity’ production. The economic constraints that influence animal welfare might be better mitigated by a regulatory system developed with greater consultation with producers, a more equitable subsidy programme, and more developed consumer-choice programmes.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".