Strategy: 为同一现象构建多个竞争假设
Scanned 6/1/2026
Install to Claude Code
npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill competing-hypothesis-construction --agent claude-codeInstalls into .claude/skills of the current project.
Are you the author of Competing Hypothesis Construction?
Add the live security badge to your README — it updates automatically with every re-scan.
[](https://www.skillsdirectory.com/skills/yogsoth-ai-competing-hypothesis-construction)More formats (shields.io, HTML) on the badges page.
---
name: competing-hypothesis-construction
description: "Strategy: 为同一现象构建多个竞争假设"
version: 1.0.0
category: hypothesis-formation
type: strategy
campaign: hypothesis-formulation
tactics:
- competing-hypothesis-matrix
sops:
- competing-hypothesis-generation
- discriminating-prediction-design
- hypothesis-comparison-matrix
- falsifiability-check
dependencies:
skills:
- context-management
- subagent-spawning
- literature-engine
---
# Competing Hypothesis Construction
为同一现象构建多个竞争假设:主动对抗 confirmation bias,通过并行构建真正不同的解释来保持认识论开放性,并设计能区分它们的判决性预测。
## 适用场景
- 研究者已有一个"偏好假设",需要主动挑战它
- 现象有多种合理解释,过早收敛会导致错误方向
- 需要向审稿人或资助方展示已考虑替代解释
- 设计实验时需要确定哪个变量最能区分竞争解释
不适用:现象已有压倒性证据支持单一解释 → 直接用 deductive-hypothesis-generation 精化该解释。
## 思维框架
**Avoid confirmation bias by generating genuinely different explanations, then find discriminating predictions**
竞争假设构建的核心逻辑:
1. **强制多样性**:竞争假设必须在机制层面真正不同,而非同一机制的变体
2. **对称对待**:每个假设都以同等严肃性对待,不允许偏好假设获得特殊待遇
3. **区分性预测**:找到能区分假设的判决性预测——什么结果支持 H1 但反对 H2,反之亦然
4. **矩阵化比较**:通过系统矩阵揭示假设间的结构性差异
**竞争假设的质量标准**:
- **真正竞争**:两个假设对同一现象给出不同的因果解释(不是同一解释的强弱版本)
- **互斥性**:至少存在一个观察结果,能支持其中一个而反对另一个
- **可比较性**:两个假设都有明确的可测试预测
## Budget Gate
| Tier | 竞争假设数 | 区分性预测 | 比较矩阵 | 可证伪性 |
|------|---------|---------|---------|---------|
| S | ≥2 个真正竞争的假设 | ≥1 个区分性预测 | 简化版(2×2) | 每个假设 1 个 falsification scenario |
| M | ≥3 个竞争假设 | ≥2 个区分性预测 | 完整矩阵(假设×预测) | 每个假设完整 falsification |
| L | ≥4 个竞争假设 | ≥3 个区分性预测 | 完整矩阵 + 实验设计建议 | 完整 falsifiability audit |
## 默认参考流
1. 调用 `competing-hypothesis-generation` SOP(via `competing-hypothesis-matrix` tactic):强制生成机制层面真正不同的竞争假设
2. 调用 `discriminating-prediction-design` SOP:为每对竞争假设设计区分性预测
3. 调用 `hypothesis-comparison-matrix` SOP:构建假设×预测比较矩阵,揭示结构性差异
4. 调用 `falsifiability-check` SOP:为每个假设生成 falsification scenario
## context-checkpoint
每轮结束后记录:
- 竞争假设清单(每个假设的核心机制声明)
- 机制差异分析(假设间在哪个层面真正不同)
- 区分性预测列表(每个预测能区分哪对假设)
- 比较矩阵(假设×预测,标注支持/反对/中性)
- 推荐的判决性实验方向
Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
No comments yet. Be the first to comment!