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.
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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.
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实测评分 未实测
查看安装方法安装前可以查看交给 AI 代理的指令内容。
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.
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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.
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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.
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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.
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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.
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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.
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