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 appraising the cumulative evidence and ensuring balance in an Academy of Management Annals (Annals) review — weighing conflicting findings by credibility, steelmanning rival schools, and handling the author's own work even-handedly. Audits evidence quality and fairness; it does not design the framework (amann-organizing-framework) or build exhibits (amann-tables-figures).
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An Annals review carries no estimates of its own — but it is not therefore neutral. The "attitude" is disciplined critical appraisal: you judge how good the cumulative evidence is, reconcile conflicts by credibility, and state where the field's confidence is and is not warranted. This is the review-craft replacement for primary-research robustness checks: you are appraising other people's designs, not defending your own.
A review must be comprehensive in coverage yet selective in emphasis — long (~50 pages) but not an inventory. Resolve the tension by tiering the corpus:
| Tier | Treatment |
|---|---|
| Foundational / field-defining | discussed in text — what it established and its limits |
| Important contributions | grouped and weighed within the framework's cells; cited with their finding |
| Confirmatory / incremental | cited in clusters ("see also …") to show coverage without bloating prose |
| Tangential | cited only where it bears on a specific claim |
Comprehensiveness is proven by the citation set (the saturation log from amann-literature-synthesis); selectivity is exercised in the prose. Equal-length summaries of every paper abdicate the editorial judgment that is the review's value.
Management findings conflict constantly. Reconcile them by why they differ, never by tally:
Occasionally a credibility judgment cannot be settled by reading alone: the review's account of a controversy hinges on whether a staggered-adoption TWFE estimate survives modern corrections, or an apparent consensus may melt once publication bias is priced in. When a load-bearing magnitude comes with a replication package, audit it rather than adjudicate by prose — the shared playbook execution-with-mcp maps each design family to callable StatsPAI / Stata MCP tools (bacon_decomposition to expose bad-comparison weighting, callaway_santanna to re-estimate, honest_did_from_result for pre-trend fragility). Any number produced this way must come from an actual run and be labelled as the review's own re-analysis. This is the exception, not the Annals default: most appraisal here stays qualitative.
Annals is the review-of-the-field: its account of a debate becomes the field's shared reference, and the surveyed authors often referee the review. Balance is therefore both ethical and strategic.
【Tiering】corpus split foundational/important/confirmatory/tangential? Y/N
【Comprehensiveness evidence】saturation log + citation set support "nothing important missing"? Y/N
【Conflict handling】reconciled by credibility + construct + context (not vote-count)? Y/N
【Evidence quality】strong/mixed/thin stated per claim? Y/N
【Steelman】each rival school stated at its strongest? Y/N
【Self-citation audit】own work at warranted tier; emphasis identity-blind? Y/N
【Attitude labelled】provocative reads marked as author's judgment? Y/N
【Next skill】→ amann-tables-figures (who-found-what tables + framework figure)
まだレビューはありません。使ってみた感想をお寄せください。
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。