aejpol-topic-selection — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited aejpol-topic-selection (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
AEJ: Policy publishes the economic analysis OF policy: a paper is built around a policy question ("should this tax / mandate / subsidy / regulation exist, expand, or change, and at what welfare cost?") whose answer carries a welfare, cost-benefit, or distributional implication of broad interest to the AEA readership. Two halves must both be present from the first page:
Public economics & taxation · environmental & energy · health · education · labor & social insurance · regulation & antitrust · development policy · political economy of policy. Empirical (quasi-experimental / RCT) and applied-theory work both fit — provided the policy question and welfare relevance are explicit.
| If the paper is mainly… | It belongs at… | Tell |
|---|---|---|
| broad-interest policy question + credible causal evidence + welfare reading | AEJ: Policy | the policy lesson is the headline |
| a deep field-public-finance contribution for specialists | J. Public Economics | broad readership would not follow the "so what" |
| identification-driven applied micro with no policy lever / welfare claim | AEJ: Applied | the natural experiment, not a policy, is the point |
| a first-order, general-interest result warranting top-5 length | AER | the contribution is larger and longer than a field-leading policy paper |
Before investing in a draft, answer these in one sentence each; a "no" or "I can't" on any is a fit problem:
A draft estimates that a state's expansion of a childcare subsidy raised maternal employment. As "we find subsidy → employment" it is a clean applied-micro result (AEJ: Applied). Reframed for AEJ: Policy: "Is expanding the childcare subsidy a cost-effective way to raise maternal labor supply, and who bears the cost?" — now the employment elasticity feeds a cost-per-additional-worker and an incidence split across income groups (illustrative), and the paper has a policy lever, a counterfactual, and a welfare reading.
【Policy lever】instrument + affected population (one sentence)
【Policy question】stated as a question with a welfare/cost-benefit/distributional stake
【Counterfactual】what the policy is compared against
【Welfare object to report】MVPF / cost-per-X / incidence / calibrated welfare
【Fit verdict】AEJ: Policy vs JPubE / AEJ:Applied / AER + one-line reason
【Next step】aejpol-literature-positioning~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.