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 systematically gathering, coding, and synthesizing a management/organization literature for an Academy of Management Annals (Annals) review — the search-and-coverage methodology and the choice of narrative vs. systematic vs. bibliometric integration. Builds the corpus and synthesis notes; it does not impose the organizing spine (amann-organizing-framework) or write prose.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
실행 점수 미검증
설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
The folder name says "data analysis," but an Annals review reports no data of its own. Your "analysis" is the systematic appraisal and integration of a literature. The credibility of the whole review rests on the reader's belief that you read everything that matters and coded it consistently. Build coverage as a transparent process, not from memory.
| Method | What it does | Best when |
|---|---|---|
| Narrative / integrative review | reads, interprets, and reorganizes the literature into a new framework | the contribution is conceptual integration (Annals' core mode) |
| Systematic review | a pre-specified, reproducible search-and-screen protocol; transparent inclusion | the field is large and you must prove comprehensive, unbiased coverage |
| Bibliometric / meta-analytic | co-citation, co-word, or quantitative effect-size synthesis | the contribution is structural (intellectual map) or a cumulative magnitude estimate |
Most Annals reviews are integrative narrative with a systematic backbone: a transparent search establishes coverage, and the narrative does the reorganizing. Bibliometrics can support the framework but rarely replaces the interpretive contribution.
amann-evidence-standards and the referees.Summarizing restates each paper; synthesizing makes papers talk to each other. Code the corpus as you read:
| Column | What to capture |
|---|---|
| Study | author–year; the contribution you cite it for |
| Construct / question | exactly what it theorizes or measures (so incommensurable work is not pooled) |
| Theory base | the lens it uses (so you can map streams and detect silos) |
| Method / context | design, sample, setting (so you can weight credibility) |
| Finding / claim | direction + magnitude or the conceptual move |
| Tension | which work it agrees/conflicts with, and why |
This matrix feeds the organizing framework, the synthesis tables, and the even-handed treatment of debates. You appraise the studies (you are the field's reviewer-of-record); you do not re-run or "correct" them.
【Method】narrative-integrative / systematic / bibliometric — and why
【Seed set】<canonical + proposal references>
【Search record】terms / databases / dates / counts logged? Y/N
【Snowball】backward+forward iterated to saturation? Y/N
【Inclusion logic】stated and consistently applied? Y/N
【Frontier + adjacency】recent WPs + bordering fields included? Y/N
【Saturation evidence】<where searches stopped yielding new must-cites>
【Coding matrix】construct/theory/method/finding/tension rows ready? Y/N
【Coverage risks】<any author/stream an omission referee could name>
【Next skill】→ amann-organizing-framework (impose the integrative spine on the matrix)
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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.