How effective are behavioral interventions to increase the take‐up of social benefits? A systematic review of field experiments
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Non‐take‐up of social benefits is a significant policy issue caused by factors such as lack of awareness, compliance costs, and stigma. While public information campaigns, default options, and in‐person assistance are increasingly used, their effectiveness remains poorly understood. This study provides a systematic review of field experiments evaluating nudges and simple behavioral interventions on program take‐up. We analyzed 93 interventions from 35 studies published over nearly 20 years, predominantly focusing on major U.S. programs. We compared study characteristics, including sample and intervention types, and assessed study quality. Due to high heterogeneity, we did not conduct a meta‐analysis but used forest plots and thematic summaries instead. Most studies reported a positive impact on program take‐up, but not on program application. Two types of interventions were notable for their impact on program application and take‐up: 1) providing and framing information; and 2) providing assistance. We discuss the limitations of this review, including the cost and safety of nudges and the implications of focusing on field experiments. We conclude that further research is needed on simpler interventions outside the U.S., as well as on compliance and psychological costs. Additionally, improving the quality and transparency of field experiments is essential.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 it