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.
中文简介正在准备中。当前显示原文说明。
Use when deciding whether an anthropology project fits American Anthropologist (AA) and which section to target. AA is the four-field AAA flagship, so the test is significance across anthropology (sociocultural, archaeology, biological, linguistic), not single-subfield novelty. Helps frame the question and pick a section; it does not collect data or conduct fieldwork.
中文简介正在准备中。当前显示原文说明。
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。
AA is the flagship four-field journal of the American Anthropological Association. The bar is not "new to my subfield" — it is "matters to anthropology broadly." A great paper makes a finding in sociocultural, archaeological, biological, or linguistic anthropology legible and useful to readers in the other fields. Use this skill to pressure-test fit and section before you invest.
A strong AA paper usually clears all four:
amanthro-research-design).amanthro-transparency-and-data).| Home subfield | Reach to four-field anthropology by… |
|---|---|
| Sociocultural | draw the portable concept/mechanism, not just the ethnographic particular; speak to theory others can use |
| Archaeology | connect material/temporal evidence to general claims about social life, not only site chronology |
| Biological / physical | tie human-variation or evolutionary findings to social and cultural meaning, not biology alone |
| Linguistic | show what the language data reveal about culture, power, or cognition beyond the grammar |
| Reflexive / public | make the methodological/ethical/political stake one the whole discipline shares |
amanthro-tables-figures).【Question】one sentence
【Four-field reach】who outside the subfield cares, and why
【Contribution type】concept / reframing / decisive case / corrected record
【Section】Research Article / Vital Topics / World / Public / Multimodal / Review Essay
【Ethics flag】any consent / community-accountability / heritage issue to design for now?
【Fit verdict】strong / needs reframing / off-fit (why)
【Next】amanthro-literature-positioning
../../resources/external_tools.md — data/archives/lab sources by subfield../../resources/official-source-map.md — AA sections and scope还没有评价。欢迎分享你的使用感受。
无需登录即可发表。欢迎分享使用感受、提问,或说明在哪些环境下无法运行。
还没有评论。来写第一条吧。
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.
中文简介正在准备中。当前显示原文说明。
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.
中文简介正在准备中。当前显示原文说明。
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.
中文简介正在准备中。当前显示原文说明。
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.
中文简介正在准备中。当前显示原文说明。
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.
中文简介正在准备中。当前显示原文说明。
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.
中文简介正在准备中。当前显示原文说明。