nbr-qualitative-case
Use for qualitative theory-building submitted to 《南开管理评论》 (Nankai Business Review) — multi-case comparison (replication logic, case selection), grounded-theory coding (open / axial / selective), theoretical saturation, and trustworthiness (data triangulation, member checking, audit trail). Use when the contribution is built inductively from cases or interviews rather than from survey/experiment data.
npx skills add brycewang-stanford/Awesome-Journal-Skills --skill nbr-qualitative-case --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.
# 质性与多案例(nbr-qualitative-case) ## 触发时机 - 用**多案例比较**或**单案例纵向**建构理论 - 用**扎根理论**从访谈/档案中归纳命题 - 现象新颖、缺成熟构念,无法直接量表化 ## 案例选择与逻辑 - 说清**选择逻辑**:理论抽样(typical / extreme / polar),不是方便取样 - 多案例用**复制逻辑**(literal / theoretical replication),而非统计抽样 - 交代案例数与边界、数据来源(访谈、档案、观察、二手)与时间跨度 ## 单案例还是多案例(先定设计) | 情形 | 设计 | 理由 | |------|------|------| | 过程机理、罕见/极端现象 | 单案例纵向 | 深描演化阶段与机制 | | 构念间关系的模式归纳 | 多案例(常 2–4 个)比较 | 复制逻辑提升可信度 | | 现象新、构念未明 | 扎根理论(不预设框架) | 从资料归纳范畴 | 选错设计是质性稿最早被毙的原因之一:用单案例宣称"普遍规律",或多案例各讲各的故事,都难过本刊外审。 ## 走查示例:老字号数字化转型双案例 设想稿件取两家百年老字号(一家转型重生、一家停滞)作极性比较: 1. 抽样逻辑写明 polar types——不是"恰好认识这两家" 2. 数据:高管访谈 30 余人次、内部档案、门店观察,三角验证;时间跨度覆盖转型前后 3. 编码产出证据链,例如: ``` "老师傅不肯用扫码点单,说砸招牌"(原始引文) → 技艺身份防御(一阶概念) → 传承-变革张力(二阶主题) → 组织身份重构(聚合维度) ``` 4. 跨案例比较:重生案例出现"身份再叙事"机制而停滞案例缺失——据此提炼命题 5. 饱和依据:第 26 次访谈后连续多次未再出现新范畴,明示于文中 ## 扎根编码(开放—主轴—选择) - **开放编码**:贴近资料生成初始概念/范畴 - **主轴编码**:建立范畴间关系(条件—行动—结果) - **选择编码**:提炼核心范畴,串起故事线与理论框架 - 展示**编码示例与证据链**(引文 → 概念 → 范畴),让推断可追溯 ## 理论饱和与可信度 - **理论饱和**:新增资料不再产生新范畴/关系,需明示判断依据 - **可信度(trustworthiness)**: - 可信性(credibility):三角验证、被试反馈(member checking) - 可迁移性(transferability):厚描述(thick description) - 可靠性(dependability)/可确认性:**审计追踪**、双人编码与一致性(如 Cohen's κ) ## 自检清单 - [ ] 案例/受访者选择是理论抽样,逻辑写清 - [ ] 多案例用复制逻辑
- 触发时机
- 案例选择与逻辑
- 单案例还是多案例(先定设计)
- 走查示例:老字号数字化转型双案例
- 扎根编码(开放—主轴—选择)
- 理论饱和与可信度
- 自检清单
- 反模式
- 数据结构与证据呈现惯例(校准锚)
- 评审挑战与对策
- 输出格式
What does the nbr-qualitative-case skill do?
Use for qualitative theory-building submitted to 《南开管理评论》 (Nankai Business Review) — multi-case comparison (replication logic, case selection), grounded-theory coding (open / axial / selective), theoretical saturation, and trustworthiness (data triangulation, member checking, audit trail). Use when the contribution is built inductively from cases or interviews rather than from survey/experiment data.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill nbr-qualitative-case --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.