The development of “roughness” in the play fighting of rats: A Laban Movement Analysis perspective
Bibliographic record
Abstract
With increasing age, rats, when play fighting, become rougher. In part, this change can be accounted for by the increasing likelihood of using adult-typical fighting tactics. However, even when using the same tactics, adults appear rougher than juveniles in their play. In this study, videotaped sequences of play fighting in rats from the juvenile (30 days) to the post-pubertal (70 days) period were analyzed using Laban Movement Analysis (LMA). Movement qualities called Effort Factors in LMA captured the character of some of this change. Juveniles tended to use Indulging Efforts, whereas older rats tended to use Condensing Efforts. The latter are related to performing movements that are more controlled. This greater level of control was also evident in the way older rats maintained postural support during play fights. When standing over supine partners, juveniles are more likely to stand on the partner with all four paws, reducing their postural stability, and hence ability to control their partner's movements. Older rats are more likely to place their hind paws on the ground, thus providing a firmer anchor for movements with their upper bodies and forepaws. These age-related changes in behavior were found for both males and females. The findings lend support to a growing body of evidence that play fighting in the juvenile phase of rats is not just a more frequently occurring version of that present in adults, but rather, has unique organizational properties.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".