The complex relationship between welfare and reproduction in cattle
Bibliographic record
Abstract
Using reproduction parameters as indicators for cattle welfare has limitations and, at best, these parameters should only be viewed as indirect indicators of welfare. On a farm level, measures such as fertility rates emphasize biological performance of the herd but fail to consider the welfare of individual animals. Even on an individual level, the relationship between reproductive effectiveness and animal welfare is complex. Good reproductive performance does not automatically signify good welfare, as domestication and targeted breeding programmes have led to prioritization of high productive and reproductive performance in most modern farm animal species. In this review, we synthesize literature regarding cattle husbandry, reproduction, welfare and their multidimensional relationships. We argue that practices such as artificial insemination or the use of sexed semen may provide potential welfare advantages as these practices reduce the risk of disease transmission and injury or enable selection of specific beneficial traits. Furthermore, they may offer a solution to current practices jeopardizing welfare, such as the management of surplus bull calves in the dairy industry. Conversely, the animals' ability to perform natural behaviours such as oestrous expression, an aspect arguably contributing to welfare, is often limited on commercial farms; this limitation is particularly evident in housing systems such as tie stalls where movement is restricted. Moreover, common management practices such as oestrus manipulation may lead to negative attitudes in citizens who often regard naturalness as important element of animal welfare.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".