Exploring dairy heifers’ consistency in social motivation in the absence or presence of conspecifics
Bibliographic record
Abstract
Cattle are motivated to maintain social contact, but individual preference for social proximity (i.e., 'sociability') varies among individuals. Although personality traits, like sociability, are generally considered to be consistent across context and time, different social environments may elicit different behavioral responses in individuals. We tested individual differences in social motivation with and without the presence of conspecifics, and compared responses within and among different social contexts. Specifically, Holstein heifers (n = 36) were exposed to standardized social isolation tests (novel arena, novel object, runway test; each tested twice, 14 days apart) and a novel social-feed trade-off paradigm. In addition, heifers were subjected to a distribution test in which groups of three animals could freely move between two feed troughs. At one trough, heifers were offered 150 g of grain every two minutes (high side) and every four minutes at the other trough (low side). We expected animals to disperse proportionally to resource availability, corresponding with the Ideal Free Distribution theory (IFD), and that deviations from IFD would reveal individual differences in motivation to be with peers. We found no consistency in sociability measures derived from behaviors in the absence (vocalization, runway latency) and presence (feeding time, social-feed trade-off score) of conspecifics. Moreover, behaviors showed low repeatability within the same social contexts. We conclude that individual differences in sociability are likely context-dependent. We suggest that sociability might not be a single 'trait', but rather a 'behavioral consequence' resulting from the combined effects of internal characteristics (e.g., other personality traits such as fearfulness) and external factors (e.g., testing environment) at the time of evaluation.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".