The Limitations of Defaults
Bibliographic record
Abstract
Prior research has demonstrated that defaults have a powerful influence on economic outcomes in a wide range of settings because individuals often passively accept default options. This paper examines the degree to which defaults become less powerful as they become more extreme. We study a firm with a defined contribution retirement savings plan in which employees are automatically enrolled at a 12% contribution rate, a rate that is considerably higher than those studied in previous work. In addition, the default contribution rate is suboptimal for all employees because the firm only matches employee contributions between 12% and 18% of pay. Approximately one-quarter of employees at this firm remain at the default contribution rate after twelve months of tenure, while the comparable fraction for firms with more modest defaults is more than 60%. We also find that employees who remain at the default contribution rate after twelve months of tenure have lower incomes than would be predicted by the incomes of employees who actively choose neighboring contribution rates. This evidence suggests that defaults are more influential for low-income employees than for high-income employees because low-income individuals generally face higher barriers to active decision-making.
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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 | 0.185 | 0.587 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.007 | 0.014 |
| Open science | 0.007 | 0.007 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.086 | 0.012 |
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".