A survey of management practices that influence production and welfare of dairy cattle on family farms in southern Brazil
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A survey on dairy production in family dairy farms in the northwest of Santa Catarina, Brazil, was carried out to assess husbandry practices and elements of the living environment that may influence animal welfare and productivity. Three farm systems common in the region were compared: extensive, pasture-based, and semi-intensive. Data were collected through face-to-face interviews with farmers, followed by an inspection of the production environment and of dairy cows on 124 dairy farms. Some welfare and production problems were common to the 3 systems, mainly subclinical mastitis and tick infestations, which affected one-third of cows, deficiencies in the provision of drinking water and shade, and poor hygiene practices during milking. Some problems were specific to farming systems, such as lameness and hock injuries on the semi-intensive farms, and inadequate milking infrastructure and greater frequencies of cows with low body condition scores on extensive and pasture-based farms. A greater proportion of farms in the semi-intensive group had modern, herringbone-type milking parlors, applied the California Mastitis Test, and followed teat disinfection practices, and more pasture-based farms provided shade in the paddocks. The widespread use of pasture and adapted genotypes and individual identification of animals were positive aspects present in all systems. The absence of health and production records in more than half of the farms may prevent farmers from recognizing certain problems. Results of this survey may guide public policies aiming to improve milk productivity and quality with sustainable and low-cost production practices.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it