Prepares criminology manuscripts for submission to the Criminology journal, covering topic selection, theory building, research design defense, data analysis (count models, trajectories, survival), APA formatting, bias-free language, anonymization, and revise-and-resubmit responses.
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Use when executing and reporting the analysis for a Criminology (ASC / Wiley) manuscript so it survives expert review — honest uncertainty, robustness, and methods appropriate to crime counts, longitudinal panels, trajectory models, and recidivism survival. Guides analysis norms; it does not fabricate results.
Use when preparing the data, replication, and transparency materials for a Criminology (ASC / Wiley) manuscript — data-availability statements, reproducibility packages, preregistration, and handling restricted criminal-justice data under DUAs. Criminology operates under growing open-science norms (Wiley open-science badges, ICPSR/NACJD archiving). Prepares the package; it does not waive requirements.
Use when positioning a Criminology (ASC / Wiley) manuscript against the literature so it reads as a contribution to the field's live debates, not a citation pile. Criminology readers expect engagement with the relevant theoretical tradition and the closest prior empirical work across the field's many disciplines. Stakes the contribution; it does not write the lit review.
Use when writing the response to a Criminology (ASC / Wiley) revise-and-resubmit. Criminology revisions usually require converting multiple expert reviewers across the field's disciplines while keeping the editor confident the revision is convergent and the theoretical contribution intact. Structures the response letter; it does not fabricate new results.
Use when defending the research design of a Criminology (ASC / Wiley) manuscript — causal identification for quantitative work, longitudinal and life-course designs, criminal-career and trajectory methods, place-based and experimental designs, or case selection and process tracing for qualitative work. Criminology judges each tradition on its own terms. 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.
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