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.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when deciding whether a project is the ONE crisp, important, well-identified insight that an American Economic Review: Insights (AER: Insights) short-format manuscript requires, rather than a multi-result paper for AER or a field paper for the AEJ family. Tests single-insight fit; it does not run the analysis.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
AER: Insights publishes short, self-contained papers built around a single important, well-executed idea. The decision is not "is this good?" but "is there exactly ONE crisp, surprising, well-identified insight that can stand alone in a short paper at AER-level importance?" Three filters:
| Symptom | Better venue |
|---|---|
| Multiple inter-dependent results that need each other | AER (long, multi-result flagship) |
| One result but field-specific, not general interest | AEJ: Applied / Micro / Macro / Policy |
| Incremental / a robustness note on existing work | a field journal or a comment |
| Pure methods with no substantive payoff in a short paper | a methods/econometrics journal |
aeri-identification) — a clean insight with a shaky design is not publishable short, because there is no room to defend a weak design.| Archetype | The single insight is… | Failure mode |
|---|---|---|
| One clean causal estimate | a single headline effect from a credible design | reporting every heterogeneity split in-text |
| A striking new fact / measurement | one important fact a non-specialist did not know | a descriptive paper with no single takeaway |
| A sharp theory result | one surprising theorem / impossibility | a general framework with the result as a corollary |
| A method that flips an answer | the substantive answer it changes, in few pages | the method shown without a substantive payoff |
A fictional project has (a) a clean RCT effect of posted wages on women's applications, (b) a heterogeneity split by occupation, and (c) a structural extension on wage offers. The AER: Insights paper is (a) alone — one surprising, general-interest, cleanly identified effect. (b) and (c) go to the Supplemental Appendix or a separate paper. Compressing all three into one short paper would be a "mini-AER" and likely a reject; the discipline is to make (a) the entire paper and defend it superbly in few pages.
If you cannot pass all three filters — single insight, AER-level importance, self-containment — the honest
move is to route elsewhere (AER for multi-result, an AEJ for field interest) rather than force-fit. The
fast, no-R&R process (aeri-referee-strategy) punishes a borderline
fit with a quick reject.
【One-sentence insight】<single headline object>
【Importance】why a non-specialist cares (general interest, AER-level)
【Prior overturned】<belief the result corrects>
【Fits short format?】core argument under cap, rest to appendix? [Y/N]
【Venue check】AER: Insights vs AER vs AEJ — chosen because […]
【Next step】aeri-literature-positioning
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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.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
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.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
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.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
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.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
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.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
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.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.