The impact of Daylight Saving Time on dog activity
Bibliographic record
Abstract
While most studies on Daylight Saving Time (DST) focus on human sleep and well-being, there is a dearth of understanding of how this sudden, human-mitigated change affects the routines of companion animals. The objective of this study was to assess how DST influenced the morning activity pattern of dogs (Canis familiaris). We used accelerometers to record activity in 25 sled dogs and 29 caregiver-companion dog dyads located in or near Ontario, Canada during the Fall Back time shift. We looked at morning onset activity based on sunrise time (both groups), handler arrival time (sled dogs), and caregiver Got-up Time (companion dogs), and compared pre-DST measures with the three days following DST. We found that sled dogs were less active around sunrise in all post-DST days compared to pre-DST, as sunrise coincided with handler arrival time before DST but not after. Companion dogs showed no change in morning activity based on sunrise times before and after DST. On the Sunday of DST, sled dogs were more active before handlers arrived, but their activity returned to pre-DST levels in the following two days. Caregiver and companion dog activities did not change on the day of DST. After DST, caregivers woke up earlier on weekdays, but companion dogs maintained their pre-DST activity patterns. Overall, we found that sled dogs took one day to adjust to a change in handler arrival time yet neither companion dogs nor their caregivers showed any morning activity difference after the Fall Back DST transition. In summary, our findings highlight the importance of flexible routines and gradual changes in helping dogs adjust to abrupt schedule modifications, offering valuable insights for optimizing dog care practices during time shifts.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".