cie-institutional-background — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited cie-institutional-background (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
本刊实证工程化,识别的合法性几乎全押在制度细节上。处理时点、处理对象、分配规则讲不准,后面所有 DID / event-study 都站不住。这也是高频拒稿/退修点。
cie-robustness)cie-did-identification)把制度背景按"可不可核查、接不接识别"分级,红格即高危退稿点。
| 要素 | A 级(可核查、接识别) | C 级(高危) |
|---|---|---|
| 政策文件 | 全称+发文机关+文号+时间 | "国家出台了相关政策" |
| 执行时点 | 逐批落地时点,与数据期对齐 | 时点含糊 / 用发文年当处理年 |
| 处理对象 | 城市/行业/企业名单 + 来源 | "部分地区""一些企业" |
| 分配规则 | 遴选标准并接平行趋势论证 | 只字未提,外生性无依据 |
| 政策内容 | 对应理论机制的具体环节 | 罗列文件原话不接机制 |
本刊把识别合法性押在制度细节上,C 级要素是高频退修/拒稿触发点;具体尺度以编辑部最新审稿标准为准。
示意冲击为"智能制造试点示范",常见误区是当成一次性政策。规范写法:
cie-robustness),并在 event-study 中检验平行趋势。cie-did-identification)。【政策】<文件名 + 发文机关 + 时间>(可核查 √ / 待核实)
【处理时点】<单一 / 分批:批次+时点>
【处理对象】<范围 + 名单来源>
【分配规则】<外生论证强 / 弱 → 需 PSM/趋势控制>
【接识别】交错 □ 预期效应 □ 平行趋势风险 □
【下一步】cie-did-identification~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.