cie-fit-positioning
Use to judge whether a manuscript fits 《中国工业经济》 (China Industrial Economics) before drafting, and to re-route if it is theory-heavy (→经济研究 / 经济学季刊), management/case/survey (→管理世界), finance-mechanism (→金融研究), or trade/open-macro (→世界经济). The journal wants empirical engineering, not pure theory or practice notes.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill cie-fit-positioning --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# 匹配度判断与改投（cie-fit-positioning） ## 触发时机 - 不确定稿子该投《中国工业经济》还是别的经济学/管理学刊 - 理论模型很重，但实证较薄——担心被嫌"有方法无思想"或"理论照搬" - 稿子像政策汇报 / 行业研究报告 / 管理案例 - 数据有了但没有干净的政策冲击 ## 本刊画像（一句话） **"理论顶天，实践立地"的产业经济实证顶刊**：要干净的中国政策准实验、做满的稳健性、机制+异质性、可落地的产业政策含义。比《经济研究》更"实证工程化"，比《管理世界》更偏经济学计量。 ## 匹配信号（命中越多越对口） - 用中国政策做准实验：试点、补贴、环保督察、宽带中国、低碳城市、自创区、数据要素、智能制造…… - 落点在**产业组织 / 企业行为 / 创新研发 / 全要素生产率 / 数字化转型 / 区域经济 / 环境规制** - 有清晰的处理组/对照组与时点，能上
What does the cie-fit-positioning skill do?
Use to judge whether a manuscript fits 《中国工业经济》 (China Industrial Economics) before drafting, and to re-route if it is theory-heavy (→经济研究 / 经济学季刊), management/case/survey (→管理世界), finance-mechanism (→金融研究), or trade/open-macro (→世界经济). The journal wants empirical engineering, not pure theory or practice notes.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill cie-fit-positioning --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From brycewang-stanford/Awesome-Journal-Skills, a repository with 909 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.