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 anticipating the objections a sophisticated American Economic Journal: Applied Economics (AEJ: Applied) referee will raise, so a manuscript pre-empts them before submission or addresses them in revision. Plans the defense; it does not draft the response letter (aeja-rebuttal) or run the submission preflight (aeja-submission).
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: Applied uses single-blind review through the AEA ScholarOne system: author identities are visible to referees, while referee identities remain anonymous to authors. An editor assigns the paper to a coeditor or handles it directly, and before a first R&R the handling coeditor consults a second coeditor. Referees here are identification-literate applied microeconomists; the modal report attacks the credibility of the design first, then magnitude/mechanism, then external validity. The editor weighs whether the contribution is novel and the design clears the bar. Plan to pre-empt the predictable objections in the paper itself, leaving the response letter for genuinely new asks.
| Referee objection (by design) | Pre-emption to build in now |
|---|---|
| "TWFE is biased under staggered timing" | heterogeneity-robust estimator + Bacon decomposition already in the paper |
| "Parallel trends is not credible" | clean pre-trend leads + honest-DID sensitivity bound |
| "Instrument is not excludable" | institutional + theoretical exclusion argument + falsification tests |
| "RD jump is manipulation / bandwidth-driven" | density test + bandwidth sensitivity + donut |
| "Effect is just selection / confounding" | Oster δ / coefficient-stability bounds |
| "Local/ITT effect ≠ the policy-relevant effect" | explicit estimand + calibrated external-validity discussion |
| "Inference too narrow (few clusters)" | wild-cluster bootstrap / randomization inference |
| "Mechanism is a black box" | a test that distinguishes the proposed channel from rivals |
| "Not reproducible" | the openICPSR package built and referenced (aeja-replication-package) |
The shared, venue-neutral objection catalog is in
../../resources/README.md(links to the empirical-methods hub) — walk it before drafting.
【Front matter】single-blind title/byline and disclosures ready? [Y/N]
【Objection map】per assumption: [objection → pre-emption in paper]
【Biggest weakness】addressed in text? [Y/N] — how: ___
【Robustness placement】main vs appendix split: ___
【External validity】estimand + scope stated? [Y/N]
【Reproducibility visible】package referenced? [Y/N]
【Next step】aeja-submission
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。