This skill is based on the negative case analysis method of Lincoln & Guba (1985) and the theoretical sampling logic of Charmaz (2014), assisting researchers in systematically identifying cases inconsistent with the current proposition, and advancing proposition revision through type differentiation, rather than simply negating the proposition.
Core stance: Negative cases are not the enemy of the proposition, but its refiner. A proposition that cannot be revised by negative cases is either already a precise good proposition, or a boundaryless generalized statement.
Startup: Obtain necessary information
After triggering, collect the following information:
Required 1: Current tentative proposition
One-sentence format is best, for example:
"Among platform workers with formal employment experience as a comparison, the internal fissures in the narrative of time freedom are characterized by 'guilt over not taking orders,' revealing that the platform transfers the responsibility for managing the boundaries of working time from the organization to the individual worker."
Required 2: Key materials supporting the proposition
Can be:
- Coding list (indicating which codes support this proposition)
- Original interview excerpts (core passages supporting the proposition)
- Existing analytical memos (paste directly)
Optional 3: Inconsistencies already noticed by the researcher (if any)
If the researcher has already noticed certain materials that make the proposition unstable, mark them first, and the skill will prioritize handling them.
Optional 4: Current stage of research progress
- Early coding stage → focus on identifying 'insufficient data' types, driving theoretical sampling
- Mid-analysis stage → focus on identifying 'boundary case' types, refining the scope of the proposition
- Late theory-building stage → focus on identifying 'true counterexample' types, testing the robustness of the proposition
Execution process
After receiving the information,automatically and continuously executethe following three stages, without waiting for user confirmation at each step.
Stage one: Parsing the proposition structure
Before searching for negative cases, first parse the internal logical structure of the proposition and output:
- The proposition's conditional scope: Under what conditions does the proposition claim to hold? (explicit conditions + implicit presuppositions)
- The proposition's core mechanism: What process does the proposition claim occurs? (the A → B logical chain)
- The proposition's falsifiable points: What kind of findings would pose a threat to the proposition?
- Threat type one: The condition appears but the result does not appear
- Threat type two: The result appears but the condition does not appear
- Threat type three: The result appears but the mechanism is different
The purpose of this step is to give subsequent negative case identification a clear target, rather than vaguely searching for 'different opinions.'
Stage two: Systematic identification of negative cases
Based on the proposition structure, identify inconsistencies from the provided materials (or based on inferences about the materials), classify each inconsistency into one of the following four types, and provide corresponding handling suggestions:
Type 1: Genuine Disconfirming Case
Definition: It satisfies all antecedent conditions of the proposition, but the result is contrary to the proposition's prediction, and this cannot be explained by adjusting boundary conditions.
Identification signals：
- The interviewee possesses all the conditions claimed by the proposition
- Their behavior/feelings/narratives clearly contradict the proposition's expectations
- The researcher cannot rationalize this deviation by saying "this is a special situation"
Analysis requirements：
- Describe the specific circumstances of this case
- Explain why it is a genuine disconfirming case rather than a boundary case
- Propose a direction for proposition revision: Is it necessary to modify the core mechanism rather than only adjusting boundary conditions?
Output format：
[真反例] 案例描述：
机制威胁：该案例挑战命题中的哪个环节？
修订方向：命题可能需要如何根本性修订？
Type 2: Boundary/Limit Case
Definition: The proposition holds within a certain range of conditions, but does not hold within another range of conditions. Such cases do not negate the proposition, but rather reveal the proposition's applicable boundaries and help researchers refine the proposition's scope conditions.
Identification signals：
- The key difference between the case and the proposition's main case lies in a certain contextual condition
- After changing this condition, the result changes systematically
- The researcher can describe this difference as "when X, the proposition holds; when Y, the proposition does not hold"
Analysis requirements：
- Describe how this case differs from the main cases supporting the proposition
- Identify the "key turning condition"—what makes this case fall outside the proposition's boundary?
- Propose a direction for proposition refinement: What condition qualification could be added to the proposition to make it more accurate?
Output format：
[边界案例] 案例描述：
关键转折条件：是什么条件差异导致了不同结果？
命题精化方向：可以在命题中加入"当……时"来更准确地界定适用范围
精化后命题草稿：
Type 3: Dimensional Variation
Definition: The case appears inconsistent with the proposition, but in essence it is a manifestation of the same phenomenon at different degrees, stages, or aspects. Such cases do not negate the proposition, but rather indicate that the phenomenon described by the proposition has internal variation and may require the introduction of dimensional analysis.
Identification signals：
- The phenomenon in the case "seems to be the same thing, but with different forms of expression"
- It can be distinguished using dimensions such as intensity, frequency, time stage, and relationship type
- The core mechanism is the same, but there are differences in the form or degree of the result's manifestation
Analysis requirements：
- Describe the similarities between this case and the main cases (confirm that the core mechanism is the same)
- Identify the source of the dimensional variation (what causes the difference in manifestation?)
- Propose a direction for deepening the analysis: Is it necessary to introduce dimensional concepts into the proposition to accommodate this variation?
Output format：
[维度差异] 案例描述：
核心机制一致性：该案例与命题共享哪些核心机制？
维度来源：表现形式的差异来自哪个维度（程度/阶段/类型/关系形式）？
分析深化方向：是否需要引入维度分析来容纳这种变异？
Type 4: Insufficient Data
Definition: There are situations that could theoretically threaten the proposition, but the current materials are insufficient to determine whether it is actually a genuine disconfirming case, a boundary case, or dimensional variation. Such situations are not "no problem," but rather indicate the direction for theoretical sampling.
Identification signals：
- The researcher intuitively feels that a certain type of interviewee or situation may be inconsistent with the proposition, but there are not yet materials
- The existing materials lack comparison cases on a certain key dimension
- A certain presupposed condition in the proposition has not been systematically tested
Analysis requirements：
- Describe which theoretical threat point currently lacks material coverage
- Propose theoretical sampling suggestions: what types of interviewees or situations should be sought to fill this gap?
- Explain the impact of this gap on the current credibility of the proposition
Output format：
[数据不足] 缺口描述：目前哪个关键情境/受访者类型缺少材料？
理论抽样建议：应寻访什么类型的案例，预期会看到什么，预期找不到什么？
当前命题可信度影响：这个数据空白对命题的当前使用有何限制？
Phase 3: Proposition revision path suggestions
Based on the above analysis, provide the overall direction for proposition revision:
Revision priority ranking
List the negative cases that need to be addressed in descending order of threat level:
- True counterexamples → highest priority, may require modifying the core mechanism
- Boundary cases → second highest priority, require refining the scope of conditions
- Insufficient data → medium priority, require advancing theoretical sampling
- Dimensional differences → suggests deepening the analysis, but does not threaten the basic validity of the proposition
Revision path suggestions (by situation)
Situation A: True counterexamples are found
The proposition may require fundamental revision. Suggestions:
- Return to the data and re-examine whether the core mechanism supporting the proposition truly has direct evidence in the materials
- Consider whether the original proposition is a phenomenon under special conditions rather than a universal mechanism
- Propose a revised draft of the proposition
Situation B: Multiple boundary cases are found
The scope of application of the proposition needs refinement. Suggestions:
- Add more explicit condition qualifications to the proposition
- Consider whether it can be developed into a comparative proposition of the form "under condition A...; under condition B..."
- Propose a refined draft of the proposition
Situation C: Mainly insufficient data
The proposition is currently in a preliminarily established state and requires actively seeking challenges. Suggestions:
- Seek new cases according to the theoretical sampling suggestions
- For now, use the proposition under the premise of "within the scope of the current materials"
- Mark which key tests have not yet been completed
Situation D: Mainly dimensional differences
The core of the proposition holds, but internal differentiation is needed. Suggestions:
- Introduce dimensional analysis to accommodate internal variation in the phenomenon
- Consider whether it can be developed into a more detailed proposition that includes dimensional concepts
Output specifications
The final output of each analysis includes:
- Summary of proposition structure analysis(Phase 1 output, about 100 words)
- List of negative cases(Classified by the four types, each entry includes case description + analysis points)
- Revision path suggestions(Clearly indicate which situation the current proposition is in and give specific suggestions)
- Revised proposition draft (if applicable)
After all outputs, output the following fixed text:
The proposition revision judgment is handed over to the researcher. The final interpretation of negative cases and the final revision of the proposition must be made by the researcher. Please have the researcher judge the following questions and inform us, so that subsequent work can proceed:
- Which inconsistencies do you consider true counterexamples, and which are boundary cases?
- Do you agree with the revision direction here?
- Are there any inconsistencies you noticed in the materials but that are not mentioned here?
Relationship with other skills
| Skill | Positioning | When to use |
|---|---|---|
negative-case-finder |
Negative case identification and proposition revision | After a proposition is initially established, systematically challenge its boundaries |
thematic-analysis |
Theme identification and structuring | Once initial codes exist, they need to be organized into a thematic structure |
grounded-coding |
Code generation and category construction | Systematic codes need to be generated from raw interview material |
memo-coach |
Analytic memo guidance | You have in-depth thoughts about a proposition and need to refine them |
Recommended order of use:
grounded-coding（生成初始编码，形成初步命题）
↓
memo-coach（深化命题的分析备忘录）
↓
negative-case-finder（挑战命题，发现边界与反例）
↓
memo-coach（修订后的命题再次深化）
Negative case analysis is not an endpoint, but a cycle of proposition refinement. Each output from negative-case-finder may trigger a new round of memo-coach or theoretical sampling.
References
- Lincoln, Y. S., & Guba, E. G. (1985). Naturalistic Inquiry. SAGE. (The classic methodological source for negative case analysis: negative case analysis as a means of ensuring reliability and validity)
- Charmaz, K. (2014). Constructing Grounded Theory (2nd ed.). SAGE. (The relationship between theoretical sampling and negative cases: one goal of theoretical sampling is to actively seek challenges to a proposition)
- Bringer, J. D., Johnston, L. H., & Brackenridge, C. H. (2006). Using computer-assisted qualitative data analysis software to develop a grounded theory project. Field Methods, 18(3), 245–266. (This reference needs to be verified by you yourself)
- Miles, M. B., Huberman, A. M., & Saldaña, J. (2014). Qualitative Data Analysis: A Methods Sourcebook (3rd ed.). SAGE. (A systematic approach to handling confirming/disconfirming cases)
Language
- Default Chinese
- If the user inputs in English, output in English, and keep frontmatter field names in English