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 you must identify which theoretical conversation an Academy of Management Review (AMR) manuscript enters and how it "challenges and extends" that conversation. Positions the argument within a literature; it does NOT summarize the field (AMR punishes review-essays) and does NOT build the new theory (that is amr-theory-development).
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。
AMR is a journal of conversations. Every accepted paper enters a specific theoretical conversation and moves it. The literature section is not a catalog of who-did-what — it is the set-up of the tension your theory will resolve. Two questions govern everything:
As you characterize the conversation, define the constructs you build on or revise. Suddaby's AMR "Editor's Comments: Construct Clarity in Theories of Management and Organization" (2010, DOI 10.5465/amr.2010.0419) is the field standard: each construct needs a precise definition, scope conditions, and clear semantic relationships to neighbors. Positioning that leaves core constructs fuzzy invites the "this is a relabel" objection.
| Move | What you do |
|---|---|
| Add a missing construct | Existing theory lacks a concept needed to explain the phenomenon; you introduce and define it |
| Re-specify a relationship | A relationship treated as direct is really mediated / moderated / recursive |
| Bound a theory | You theorize the conditions under which the existing theory holds vs. fails |
| Bridge two conversations | You connect two streams that have ignored each other, generating new propositions |
| Reconceptualize a construct | You split, merge, or redefine a construct, dissolving a standing debate |
| Shift the level | A construct theorized at one level (individual) is re-theorized at another (collective) with new dynamics |
Dyer & Singh's "The Relational View" (AMR 1998, DOI 10.5465/amr.1998.1255632) is model positioning: it names two dominant conversations (the resource-based view and the industry-structure view), shows both locate competitive advantage at the wrong unit, and opens new theoretical space (relational rents accruing to dyads/networks) — challenge AND extend, by argument, with no dataset. Cite the conversation in APA-style (AOM house style).
amr-topic-selection)【Primary conversation】theory stream + seminal anchor
【Shared assumption / limit targeted】...
【Challenge】what existing theory cannot do
【Extend】the new theoretical machinery you will add
【Positioning move】add-construct / re-specify / bound / bridge / reconceptualize / shift-level
【Next step】amr-theory-development
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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。