Are Breaks Always Helpful? The Interaction of Work Breaks and Working Memory Capacity on Accounting Error Detection<sup>*</sup>
Bibliographic record
Abstract
ABSTRACT Accounting review tasks undertaken by supervisors are crucial in the discovery of discrepancies. Most individuals believe that in this context the majority of breaks taken are beneficial, rather than harmful, to work performance. This study explores the improvement that breaks can bring to accounting tasks and how individuals' working memory capacity (WMC) moderates the relationship between breaks and task performance. Through an experiment, we find that when breaks are assessed together with WMC, low‐WMC participants who took a break between tasks did not perform better on a review task than those who did not take a break. Break‐taking was most beneficial to review task performance for individuals with high WMC. Although prior break research has mostly been studied in a blue‐collar setting, exploring the impact of breaks on performance in an accounting setting is important as psychology research findings do not always translate into this context.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".