Social Signaling and Childhood Immunization: A Field Experiment in Sierra Leone
Bibliographic record
Abstract
This article explores the use of social signaling as a policy tool to sustainably affect childhood immunization. In a 26-month field experiment with public clinics in Sierra Leone, I introduce a verifiable signal-in the form of color-coded bracelets-given to children upon timely completion of the first four or all five required vaccinations. Signals increase parents' belief in the visibility of their actions and knowledge of other children's vaccine status. The impact of signals varies significantly with the cost and perceived benefits of the action. There are no discernible effects on timely and complete immunization when the signal is linked to an easier-to-complete vaccine with low perceived benefits, and large positive effects when the signal is linked to a costlier-to-achieve vaccine with high perceived benefits. Parents adjust their behavior nine months before realizing the social image benefit, demonstrating the motivational strength of signaling incentives. Of substantive policy importance, bracelets increase full immunization at one year of age by 9 percentage points, with impacts persisting at two years of age. At a marginal cost of US$24.7 per fully immunized child, social signals can be as cost-effective as financial or in-kind incentives.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".