aaai-artifact-evaluati…
Use when packaging AAAI code, data, multimedia appendices, technical appendices, reproducibility evidence, and post-acceptance artifact releases without…
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
$ npx -y skills add brycewang-stanford/Awesome-Journal-Skills --skill amann-literature-synthesis --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/amann-literature-synthesisContext preview
The summary Claude sees to decide when to auto-load this skill.
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
name: amann-literature-synthesis description: 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.
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.
1. **Seed set.** Start from the proposal's key references and the field's canonical pieces. 2. **Transparent search.** Search the major databases (Web of Science, Scopus, EBSCO/Business Source, Google Scholar) by topic keywords; record terms, databases, dates, and counts so the "Review scope and process" claims are auditable. 3. **Forward + backward snowball.** Backward: each paper's reference list. Forward: who cites the seeds. Iterate until new searches stop turning up unseen important work (*saturation*). 4. **Inclusion / exclusion logic, stated.** Define what is in and out (time window, journal tier, theoretical vs. empirical, allied fields) and apply it consistently — referees ask "why did you omit X?" 5. **Working papers + adjacent literatures.** A current review must reach recent work and the bordering fields (organizational psychology, sociology) the literature draws on, or it reads stale or siloed. 6. **Saturation log.** Record when each search stopped yielding new must-cite work — this is your evidence of comprehensiveness for `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
Stanford REAP × CoPaper.AI · 由斯坦福实证方法论团队精选与维护 访问 copaper.ai 微信:CoPaper.AI 按 11 个主流学科板块覆盖 经管与商科 社会科学 人文学科 数学与物理科学 生命科学 医学与健康 工程与技术 计算机科学与 AI 体育科学 点击任一学科名可跳转到对应说明;每类下的代表子领域在正文总览中完整列出。下方封面墙按 venue 导航,完整分类见覆盖一览。 🧭 布局指南 · 📚 Skill Pack 一览 · ⚡ 如何使用 · 🧪 自动实证
Use when packaging AAAI code, data, multimedia appendices, technical appendices, reproducibility evidence, and post-acceptance artifact releases without…
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,…
Use when preparing an accepted AAAI paper for camera-ready source submission to AAAI Press, including proceedings page limits, two-column template compliance,…
Use when designing or auditing AAAI experiments for the broad-AI program committee, including baselines, ablations, statistical significance, robustness, human…
Use when positioning an AAAI paper's novelty against archival work, contemporaneous arXiv or workshop papers, and AAAI/IJCAI/NeurIPS/ICML/ICLR neighbors across…
Use when strengthening an AAAI paper's reproducibility checklist (placed after references), experimental traceability, seed and hyperparameter reporting,…