Guides political science researchers through the full lifecycle of a Journal of Politics (JOP) manuscript — from topic selection and theory building to page-budget-constrained writing, research design defense, replication package preparation, and R&R rebuttals — with bilingual (en/zh-CN) support.
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Use for analysis-stage decisions on a The Journal of Politics (JOP) manuscript — uncertainty, robustness, and reporting norms — written so the work is reproducible from line one. JOP makes acceptance contingent on replicability and a JOP replication analyst re-runs the code, so every reported number must come from a script. Guides analysis; it does not fabricate results.
Use when positioning a The Journal of Politics (JOP) manuscript in the literature — staking a theoretically innovative, general-interest contribution while keeping the manuscript double-blind. JOP's page budget forces an efficient literature section, so engage the debates that matter without a survey. Frames the contribution; it does not write the paper.
Use when writing the response to a The Journal of Politics (JOP) revise-and-resubmit. The response must convert each reviewer without alienating the editor, stay within JOP's page budget, keep the manuscript double-blind, and preserve replicability so the eventual JOP replication-analyst check passes. Structures the response letter; it does not fabricate new results.
Use when preparing the replication / data-access materials for a The Journal of Politics (JOP) manuscript. JOP makes acceptance contingent on replicability — a JOP replication analyst assigned at conditional acceptance assesses the package you deposit in the JOP Dataverse (Harvard Dataverse), and non-replicable manuscripts are rejected. Prepares the package; it does not waive the requirement.
Use when defending the research design of a The Journal of Politics (JOP) manuscript — causal identification for quantitative work, experimental and survey-experimental design, formal-empirical linkage, or case selection and process tracing for qualitative work. JOP is methodologically diverse and makes acceptance contingent on replicability, so design with reproducibility in mind. Strengthens the design; it does not write code.
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横跨经管社科 · 人文社科 · 自然科学 · 临床医学 · AI 计算机等多个主流学科,为每一本期刊 / 每一个会议单独编码它的投稿工作流。
🧭 布局指南 · 📚 Skill Pack 一览 · ⚡ 如何使用 · 🗺 路线图 · 🌐 English
先看期刊,再进 Pack。点击任意封面即可进入对应的期刊 Skill 包。
🆕 四个最新学科广度合集 —— 工程技术 40 · 农业环境 30 · 临床医学 30 · 英文人文 36;点击封面进入合集页。
其他合集 · 中文体育学 · 12 本 CSSCI 体育学来源刊
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Agent skill stack for submitting to 《经济研究》 (Economic Research Journal), the top economics journal in China. Eighteen skills across the manuscript lifecycle: China-context topic selection, introduction, bilingual literature review, theory & hypotheses, data & sample, modern causal identification (DID / IV / RDD / DML with heterogeneity-robust estimators), mechanism analysis (post-江艇 2022 paradigm), heterogeneity, robustness, three-line tables, policy implications, abstract, house style, reviewer-lens self-audit, reproducibility, submission preflight, and R&R rebuttals. Ships a runnable Stata + Python code library. Bilingual zh-CN / en docs.
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Agent skill stack for manuscripts targeted at the Journal of Financial and Quantitative Analysis (JFQA) — empirical and quantitative financial economics (corporate finance, investments, capital and security markets, financial institutions, and finance-relevant quantitative methods), published by Cambridge University Press for the Michael G. Foster School of Business at the University of Washington. Built around the JFQA realities: submission via Editorial Manager with a text-searchable PDF, a $350 fee (only $275 refunded if not sent to a reviewer), double-anonymous review, a strict one-paragraph / 100-word abstract cap, prescriptive 8.5x11 / 1-inch / 12-pt Times New Roman double-spaced formatting, a one-year resubmission ban for undisclosed prior rejections, and the JFQA Code Sharing Policy with a dedicated JFQA Dataverse at the Harvard Dataverse. Covers topic fit, literature positioning, causal/identification design for finance, robustness, tables and figures, house style, the code/data archive, referee strategy, submission preflight, and R&R rebuttals. Bilingual en / zh-CN docs; Stata / R / Python conventions.
Agent skill stack for manuscripts targeted at the American Journal of Political Science (AJPS) — the flagship journal of the Midwest Political Science Association (MPSA), published by Wiley, submitted via Editorial Manager under double-blind peer review. AJPS is a generalist, quantitatively leaning political-science venue spanning American politics, comparative politics, international relations, political behavior, institutions, methodology, and formal theory, and it publishes Articles (<= 10,000 words), Research Notes (<= 4,000 words, methodology and meta-analysis only), and Correspondence (<= 4,000 words). The pack's signature focus is the AJPS Replication & Verification Policy: before any accepted article is published, a third-party verifier re-runs the deposited code to confirm it reproduces the numerical results in the main text — quantitative verification now performed by the Cornell Center for Social Sciences (after the Odum Institute contract ended 2023, 待核实) and qualitative verification facilitated by the Qualitative Data Repository (QDR) at Syracuse, with materials deposited to the AJPS Dataverse on the Harvard Dataverse Network. Facts covered include the 150-word abstract cap, the word-count rule (includes notes and table/figure captions, excludes references and online Supporting Information), strict author-anonymizing, the APSA Style Manual or Chicago 18th option, and the 20-page Supporting Information limit. Covers topic selection, literature positioning, theory building, research design, data analysis, exhibits, writing, the verified replication package, the review process, submission preflight, and R&R rebuttals. Bilingual en / zh-CN docs.
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