Use when anticipating how AEJ: Economic Policy referees and editors will read a manuscript, before submission or before an R&R, to pre-empt the objections that sink policy-evaluation papers. Maps likely pushback to fixes and calibrates expectations; it does not write the response letter (see aejpol-rebuttal) or fix the identification.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
AEJ: Policy reviews are single-blind through the AEA system (referees see the authors; authors do not see referees), refereed by economists who expect both credible causal evidence and a policy-relevant welfare reading. A referee typically tests four things in order; a paper dies at the first one it fails:
aejpol-topic-selection test) — a clean estimate with no policy lever or welfare reading invites a "better suited to a field journal / AEJ: Applied" rejection.aejpol-identification test) — staggered TWFE, asserted parallel trends, a weak instrument, or an over-generalized RDD are the usual kill shots.aejpol-theory-model test) — a hand-waved "this is welfare-improving" or a sufficient-statistic formula whose assumptions are violated.aejpol-robustness / aejpol-replication-package tests).| Likely referee objection | Pre-emption to build before submitting |
|---|---|
| "This isn't a policy paper / not broad-interest" | Lead with the policy question + welfare stake; state the cost-benefit reading in the abstract |
| "Staggered TWFE is biased here" | Heterogeneity-robust DID + Bacon decomposition + flat leads, in the main paper |
| "Parallel trends is assumed, not shown" | Event-study leads + honest-DID bounds |
| "Exclusion restriction is not credible" | Institutional + theoretical defense + falsification |
| "The welfare claim is hand-waved" | Explicit sufficient-statistic / MVPF / cost-benefit derivation |
| "External validity is unclear" | Heterogeneity by setting; explicit scope of the policy lesson |
| "Effect is significant but tiny / not policy-relevant" | Benchmark the magnitude against budget / status quo |
| "Not reproducible / data unavailable" | AEA-compliant package + restricted-data access path ready |
An education-policy paper using a funding-formula RDD anticipates three objections: (1) "local estimate only" → states the estimand and argues the threshold population is the marginal policy population; (2) "manipulation at the cutoff" → CJM density test + donut RDD; (3) "no welfare reading" → translates the test-score effect into a cost-per-standard-deviation and compares to class-size policies. All three answers are in the main text, so no referee can raise them as fatal.
【Broad-interest verdict】would a referee call this a policy paper? [Y/N + fix]
【Top identification objection】+ main-text pre-emption
【Welfare-reading objection】derived or hand-waved? + fix
【Objection→answer map】[objection → exhibit/paragraph]
【Fix vs. disclose list】what to fix now / what to bound and disclose
【Next step】aejpol-submission (if ready) or back to the named skill
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Use when packaging AAAI code, data, multimedia appendices, technical appendices, reproducibility evidence, and post-acceptance artifact releases without violating double-blind or immutable-supplement rules.
日本語の概要は準備中です。原文の説明を表示しています。
Use when drafting an AAAI author response (rebuttal) under the single short character-limited author-feedback window, the no-URL rule, no-new-results guidance, AI-generated-review handling, and the AAAI two-phase review process where Phase-2 papers receive one feedback round before SPC/AC discussion.
日本語の概要は準備中です。原文の説明を表示しています。
Use when preparing an accepted AAAI paper for camera-ready source submission to AAAI Press, including proceedings page limits, two-column template compliance, copyright transfer, purchased extra technical pages, deanonymization, registration, oral or poster presentation, and final public artifact release.
日本語の概要は準備中です。原文の説明を表示しています。
Use when designing or auditing AAAI experiments for the broad-AI program committee, including baselines, ablations, statistical significance, robustness, human evaluation, AI-for-Social-Impact and alignment/safety evidence, compute and cost reporting, and reproducibility-checklist alignment for Phase-1 survival.
日本語の概要は準備中です。原文の説明を表示しています。
Use when positioning an AAAI paper's novelty against archival work, contemporaneous arXiv or workshop papers, and AAAI/IJCAI/NeurIPS/ICML/ICLR neighbors across the broad AI scope, while staying inside AAAI's dual-submission and AI-as-source policy constraints and writing a related-work section legible to non-specialist reviewers.
日本語の概要は準備中です。原文の説明を表示しています。
Use when strengthening an AAAI paper's reproducibility checklist (placed after references), experimental traceability, seed and hyperparameter reporting, compute and cost disclosure, dataset access and licensing, code/data ZIP readiness, and the claim-to-evidence map that Phase-1 reviewers use to judge rigor across AAAI's broad AI scope.
日本語の概要は準備中です。原文の説明を表示しています。