When we change the clock, does the clock change us?
Bibliographic record
Abstract
The practice of standardizing the designation of time is a central device for coordinating activities and economic behaviors across individuals.However, there is nearly always conflict between an individual's goals of coordinating activities with others and engaging in those activities at their own preferred time.When time is standardized across large geographic areas, that tension is enhanced, because norms about the "clock times" of activities conflict with adapting to local environmental conditions created by natural or "solar" time.This tension is at the heart of current state and national debates about adopting daylight saving time or switching time zones.We study this conflict by examining how geographic and temporal variation in solar time within time zones affects the timing of a range of common behaviors in the United States.Specifically, we estimate the degree to which people shift their online behavior (through Twitter), their commute (using data from the Census), and their visits to businesses and other establishments (using foot traffic data).We find that, on average, a one-hour shift in the differential between solar time and clock time --approximately the width of a time zone --leads to shifting the clock time of behavior by between 9 and 26 minutes.This result shows that while adapting to local environmental factors significantly offsets the differential between solar time and clock time, the behavioral nudge and coordination value of clock time has the larger influence on activity.We also study how the trade-off differs across different activities and population demographics.
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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 | 0.003 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.005 | 0.010 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.004 |
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".