Goal Cognition at the Beginning and the End of the Day
Bibliographic record
Abstract
Across two studies, we examined whether time of day affects how humans cognitively represent personal goals. Using a within-subject design in Study 1, we found that participants reported thinking more about concrete plans for how to pursue personal goals in the morning than in the evening of the same day. In contrast, thoughts about abstract aspects of the goal, such as underlying reasons for why they have that goal, did not differ by time of day. In Study 2, we examined cognition about goals in a between-subject experiment, randomly assigning participants to report on three personal goals in the morning or the evening. Participants who completed the survey in the morning reported a greater focus on concrete goal aspects such as implementation plans than participants who completed the survey in the evening, especially among Morning Chronotypes. Focus on abstract aspects of the goal was unaffected by time of day or one’s Chronotype. In both studies, more focus on concrete plans was linked to more goal progress reported at the end of the day (Study 1) or the next day (Study 2). These studies underline the importance of considering contextual factors such as time of day when examining goal cognition.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".