2009): "Born on the First of July: An (Un) Natural Experiment in Birth Timing
Bibliographic record
Abstract
It is well understood that government policies can distort behavior. But what is less often recognized is the anticipated introduction of a policy can introduce its own distortions. We study one such “introduction effect”, using evidence from a unique policy change in Australia. In 2004, the Australian government announced that children born on or after July 1, 2004 would receive a $3000 “Baby Bonus. ” Although the policy was only announced seven weeks before its introduction, parents appear to have behaved strategically in order to receive the benefit, with the number of births dipping sharply before the policy commenced. On July 1, 2004, more Australian children were born than on any other single date in the past thirty years. We estimate that over 1000 births were “moved ” so as to ensure that their parents were eligible for the Baby Bonus, with about one quarter being moved by more than one week. Most of the effect was due to changes in the timing of inducement and cesarean section procedures. We find evidence to suggest that babies who were shifted into the eligibility period were more likely to be of high birth weight. Two years later, on July 1, 2006, the Baby Bonus was increased, and
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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 | 0.009 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".