Time for Blood: The Effect of Paid Leave Legislation on Altruistic Behavior
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Organizations and public agencies that promote pro-social activities constantly struggle to attract and encourage more contributions. In this article, we study the effects of an explicit reward in the context of blood donation. Specifically, we analyze the effects of a legislative provision that grants a one-day paid leave of absence to blood donors who are employees in Italy, using a unique data set with the complete donation histories of the blood donors in an Italian town. The across-donor variation in employment status, and within-donor changes over time are the sources of variation that we employ to study whether the paid-day-off incentive affects the frequency of their donations. Our analysis indicates that the day-off privilege leads donors who are employees to make, on average, one extra donation per year, which represents an increase of around 40%. We also find that the provision has persistent effects, with donors maintaining higher donation frequencies even when they cease to be eligible for the incentive. We discuss the implications of our findings for policies aimed at reducing the shortages in the supply of blood and, more generally, for organizations that try to motivate voluntary contributors. (JEL: D12, D64, I18)
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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