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 handling research ethics, consent, community accountability, and data/transparency for an American Anthropologist (AA) manuscript — informed consent, anonymization, protection of vulnerable interlocutors, heritage and repatriation obligations, and what (and what NOT) to share. At AA this is an ethics-and-accountability skill grounded in the AAA ethics principles and an ethics of care. Plans the ethics and transparency; it does not grant waivers.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
At AA, "transparency" is not primarily a reproducibility package — it is research ethics and accountability. The AAA's Principles of Professional Responsibility (do no harm; obtain informed consent; be open and honest; weigh competing obligations to people, communities, scholarship, and the profession) govern the work, and AA practices an explicit ethics of care in its editorial process. The single most important rule: protecting people can override sharing data. Design ethics in from the start (run this skill early and before submission).
amanthro-tables-figures).【AAA ethics】do-no-harm / consent / honesty / competing-obligations addressed? [Y/N]
【Consent】ongoing + covers publication & media use? [Y/N]
【Anonymization】strategy + limits stated; vulnerable interlocutors protected? [Y/N]
【Heritage/remains/biological】provenance + community authority + repatriation respected? [Y/N/NA]
【Data sharing】what is shared / what is ethically withheld + why
【Next】amanthro-review-process
../../resources/official-source-map.md — AAA Principles of Professional Responsibility, AA ethics-of-care statement, Wiley data policy../../../shared-resources/empirical-methods/reporting-standards.md — background reporting hygiene for quantitative (biological/archaeological) subfields only아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.
로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.
아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.
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.