The humans behind the herd: are alternative livestock farms agroecological from a socioeconomic perspective?
Bibliographic record
Abstract
In the Global North, alternative livestock farms are sometimes considered preferable to large-scale specialized farms, which are largely preeminent in current livestock supply chains. In this study, we aimed to determine if alternative livestock farms respected the socioeconomic principles of agroecology. A qualitative thematic analysis and a multivariate quantitative analysis were conducted based on data gathered from a sample of 15 farms over the course of three years. All farms raised multiple species and marketed their products through multiple different outlets, most of them directly to the end consumer, ensuring high economic diversification and connectivity. High levels of work satisfaction were commonplace, as farmers’ values were aligned with their work. Even though their sales prices were much higher than those obtained by large-scale specialized livestock farms, average net incomes and employee wages were low. Most farms operated at a small scale, but farms with higher gross incomes had higher net incomes, suggesting a certain level of economic performance due to economies of scale. Most farm characteristics were found to be in line with locally accepted social values such as gender equity, animal welfare, and providing ingredients for meat-forward diets, which are the local norm. Farmers deplored the fact that they did not have the institutional leverage to take part in territorial and food system governance. While alternative livestock farms cannot readily replace large scale specialized farms in terms of production volume, their socioeconomic characteristics were found to align with the agroecological ideal.
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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 | 0.001 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".