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 assembling the data and code deposit for an American Economic Review: Insights (AER: Insights) short-format manuscript to pass the AEA Data and Code Availability Policy and the AEA Data Editor's pre-publication reproducibility check. Builds the package and README; it does not run the analysis.
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。
AER: Insights enforces the AEA Data and Code Availability Policy, administered by the AEA Data Editor (Lars Vilhuber). Before publication, authors deposit data, code, and documentation sufficient to permit replication of every result in the paper and approved appendices in the AEA Data and Code Repository (openICPSR); the data editor's team verifies reproducibility before the paper is published. The short format does not shrink this requirement — the Supplemental Appendix results are in scope too. Build the package as you go, not after the conditional accept, because the verification step is a gate to publication.
run/00_master) that regenerates every exhibit end-to-end.aeri-robustness, aeri-theory-model) must still be reproducible.data/raw (read-only) → code → output; see ../../resources/code/ for a runnable skeleton.Because AER: Insights decisions are conditional accept or reject with no traditional R&R
(aeri-referee-strategy), a conditional accept moves quickly to the
data-editor stage. There is no long revision phase in which to build the package retroactively. Have the
deposit essentially ready at submission, so a conditional accept does not stall on reproducibility. The
data editor's check is a gate to publication, not a formality — non-reproducible code delays or blocks
the paper regardless of the editor's decision.
A fictional staggered-DiD paper has five exhibits and a dozen appendix tables. The package contains a
00_master script that runs 01_clean → 02_descriptive → 03_did_modern → 08_robustness →
09_tables, regenerating Figures 1–2 and Tables 1–3 plus every appendix table, with seeds set in the
bootstrap step. The README maps "Figure 1 ← code/03_did_modern.do, lines 40–80" and lists Stata 18 with
pinned csdid/reghdfe versions. The restricted payroll extract is described with an application link and
the exact code that would run on it. This is what passes the AEA Data Editor on the first pass.
【Master script】regenerates all exhibits + in-text numbers? [Y/N]
【README】sources / file list / versions / exhibit→code map present? [Y/N]
【Data status】public deposit / restricted (statement + access + code)?
【Seeds & versions】set and pinned? [Y/N]
【Appendix in scope】appendix results reproducible? [Y/N]
【Deposit target】AEA Data and Code Repository (openICPSR)
【Next step】aeri-referee-strategy (or aeri-submission if submitting)
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。