Mind-wandering in Larks and Owls: The Effects of Chronotype and Time of Day on the Frequency of Task-unrelated Thoughts
Bibliographic record
Abstract
People differ in their optimal time of day to perform a cognitive task: Morning people (“larks”) perform better in the morning compared to the evening, and the reversed is true for evening people (“owls”). This synchrony effect has been observed for executive functions, such as inhibitory control. For example, participants performing the Sustained Attention to Response Task (SART) make more commission errors at their non-optimal time of day. Because mind-wandering (MW) has been related to the executive system, we here investigated a synchrony effect in the frequency of MW. After determining the participants’ chronotype (n = 130), they completed an online version of the SART twice, once in the morning and once in the evening. MW was subjectively measured using a probe-caught method. Results showed that “larks” mind-wandered more often in the evening than the morning session. In contrast, “owls” showed the opposite profile. Objective markers for MW (i.e., accuracy and reaction time coefficient of variance) confirmed these results. Furthermore, in line with earlier suggestions, the frequency of MW was also directly related to the number of hours slept the night before the experiment, and an overall higher frequency of MW was observed for evening chronotypes. The results of this study provide clear evidence for the relation between sleep-related factors and MW, and raises the importance of accounting for chronotype differences when scheduling work and academic activities.
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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 | 0.000 |
| 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".