Use when running the final pre-submission preflight for the American Economic Journal: Macroeconomics (AEJ: Macro) via the AEA submission system — membership-scaled fee, JEL codes, PDF and length rules, ≤100-word abstract, disclosure statements, and data/code readiness. Final checks; it does not draft content.
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aejmac-replication-package). Field experiments register in the AEA RCT Registry.【Format】PDF; title page; JEL + keywords? [Y/N]
【Abstract】≤100 words? [Y/N] (current: __)
【Length】within ~40pp guidance (incl. appendices) or appendix split planned? [Y/N]
【Fee】member/nonmember × income tier determined; card ready? [Y/N]
【Disclosure】separate statement per coauthor; $10k threshold checked? [Y/N]
【Data/code】replication package staged for the AEA Data Editor? [Y/N]
【Next step】submit via the AEA system → aejmac-referee-strategy for what to expect
templates/checklist.md — 8-section pre-submission self-check../../resources/official-source-map.md — official AEA URLs behind every factNo reviews yet. Tell others what you thought.
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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.
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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.
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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.
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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.
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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.
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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.
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