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 the contribution of an American Economic Journal: Microeconomics (AEJ: Micro) manuscript is fuzzy or oversold relative to the closest existing results. Stakes the theorem-relative delta against the nearest theory; it does not build the model (see aejmic-theory-model) or frame the prose (see aejmic-writing-style).
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。
For a theory-first journal, positioning is theorem-relative: identify the closest existing result and state precisely the delta — what your model relaxes, generalizes, characterizes, or overturns. Vague "we contribute to the literature on X" framing is the most common avoidable weakness. AEJ: Micro referees are subject-matter experts; they know the nearest theorem and will measure your delta against it.
Position against the theory frontier (mechanism design, IO theory, information economics, decision theory…), not against empirical applied-micro papers — that signals an AEJ: Applied framing. If your result has an empirical or experimental companion literature, cite it as motivation, not as the bar your contribution clears.
| Delta type | What it looks like | What the reader must see |
|---|---|---|
| Weaker assumption | Same conclusion, fewer/looser hypotheses | The dropped assumption named; that the old proof breaks without your argument |
| New environment | Old mechanism, richer setting (search, networks, dynamics) | What the new setting adds that the old result could not capture |
| Full characterization | Prior work had a special case or sufficiency only | Both directions; the boundary of the characterization |
| Impossibility / no-go | Prior work conjectured or assumed possibility | The exact obstruction and which primitive causes it |
| New mechanism | Same phenomenon, different economic force | Why the new force is the right explanation |
State which row you are in in the contribution paragraph — a referee who cannot classify your delta will undervalue it.
If a close result appeared independently and around the same time, acknowledge it explicitly and state the relationship (different method, complementary result, prior circulation date). Silence here reads as either ignorance or concealment to an expert referee.
A persuasion paper says it "extends the Bayesian-persuasion literature." A referee asks how it differs from the canonical single-sender result. The fix: "Closest is the single-sender concavification result; we relax commitment to partial commitment and characterize the sender-optimal signal, which coincides with full commitment only when the state space is binary." That one sentence is the delta — environment relaxed (partial commitment), full characterization, and an explicit scope limit (coincides only in the binary case).
【Closest result】[Author, Year]: shows [P] under [assumptions A]
【Our delta】[weaker assumption / new environment / characterization / impossibility / new mechanism]
【Not improved】[explicit scope limit]
【Anchor map】3–6 papers, one clause each
【Frontier check】positioned against theory, not empirics? [Y/N]
【Next step】aejmic-theory-model (build/sharpen the result) or aejmic-writing-style (intro)
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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。