checking-theory-saturation

name	checking-theory-saturation
description	当用户需要检验扎根理论饱和度，包括新概念识别、范畴完善度、关系充分性和理论完整性评估时使用此技能
version	1.1.0
author	socienceAI.com
tags	["grounded-theory","saturation-analysis","qualitative-research","concept-identification","category-development","planning-with-files"]
compatibility	Claude 3.5 Sonnet and above
metadata	{"domain":"qualitative-research","methodology":"grounded-theory","complexity":"intermediate","integration_type":"analysis_tool","last_updated":"2026-01-23"}
dependencies	["planning-with-files"]
allowed-tools	["python","bash","read_file","write_file"]

理论饱和度检验技能 (Checking Theory Saturation)

Overview

为扎根理论研究提供科学、系统的理论饱和度检验，确保理论构建的完整性和可靠性。

When to Use This Skill

Use this skill when the user requests:

• Assessment of theoretical saturation in grounded theory
• Determination of whether new concepts are still emerging
• Evaluation of category development completeness
• Checking if sufficient data has been collected
• Validation of theoretical framework completeness
• Decision-making about ending data collection
• Assessment of concept, category, and theory sufficiency
• Evaluation of theoretical explanation adequacy
• Need for systematic planning and progress tracking in saturation analysis
• Integration with planning-with-files for project management

Quick Start

When a user requests saturation assessment:

1. Analyze new data for emerging concepts
2. Evaluate category development completeness
3. Assess relationship network stability
4. Validate theoretical explanation adequacy
5. Determine if additional data is needed

使用时机

当用户提到以下需求时，使用此技能：

• "理论饱和度" 或 "饱和度检验"
• "理论是否饱和" 或 "检查饱和度"
• "需要更多数据" 或 "补充数据"
• "可以结束研究" 或 "研究完成度"
• "理论完整性" 或 "理论完善度"
• 需要评估理论构建的充分性

脚本调用时机

当需要执行理论饱和度检验时，调用对应的脚本：

• 概念饱和检验：assess_concept_saturation.py
• 范畴饱和检验：assess_category_saturation.py
• 关系饱和检验：assess_relationship_saturation.py
• 理论饱和检验：assess_theory_saturation.py
• 综合饱和度判断：make_saturation_judgment.py

统一输入格式

{
  "saturation_context": {
    "research_topic": "研究主题",
    "current_coding_stage": "当前编码阶段",
    "theoretical_perspective": "理论视角",
    "saturation_purpose": "饱和度检验目的"
  },
  "input_data": {
    "existing_theory": {
      "concepts": [
        {
          "id": "概念ID",
          "name": "概念名称",
          "frequency": "出现频率",
          "last_appearance": "最后出现位置"
        }
      ],
      "categories": [
        {
          "id": "范畴ID",
          "name": "范畴名称",
          "attributes": ["属性列表"],
          "dimensions": ["维度列表"],
          "relationships": ["关系列表"]
        }
      ],
      "relationships": [
        {
          "id": "关系ID",
          "from": "源概念/范畴ID",
          "to": "目标概念/范畴ID",
          "type": "关系类型",
          "strength": "关系强度(0-1)"
        }
      ],
      "theoretical_framework": "理论框架描述"
    },
    "new_data": [
      {
        "id": "新数据ID",
        "content": "新数据内容",
        "type": "数据类型",
        "source": "数据来源"
      }
    ],
    "saturation_criteria": {
      "concept_threshold": 0.05,
      "category_threshold": 0.90,
      "relationship_threshold": 0.10,
      "theory_threshold": 0.90
    }
  },
  "analysis_parameters": {
    "confidence_level": 0.95,
    "statistical_significance": 0.05,
    "minimum_sample_size": 10
  }
}

统一输出格式

{
  "summary": {
    "saturation_level": "fully_saturated|partially_saturated|not_saturated",
    "overall_saturation_score": "总体饱和度分数(0-1)",
    "confidence_level": "置信度(0-1)",
    "concepts_emerging_rate": "新概念出现率(0-1)",
    "categories_development_score": "范畴发展分数(0-1)",
    "processing_time": "处理时间(秒)"
  },
  "details": {
    "concept_saturation": {
      "new_concepts_identified": [
        {
          "id": "新概念ID",
          "name": "新概念名称",
          "significance": "重要性(0-1)",
          "data_source": "数据来源"
        }
      ],
      "new_concepts_count": "新概念数量",
      "average_per_dataset": "每份数据平均新概念数",
      "significance_level": "重要性水平(high/medium/low)",
      "trend_analysis": "趋势分析"
    },
    "category_saturation": {
      "attributes_completeness": "属性完整度(0-1)",
      "dimensions_coverage": "维度覆盖度(0-1)",
      "relations_stability": "关系稳定性(0-1)",
      "category_maturity_scores": {
        "category_id": "成熟度分数(0-1)"
      }
    },
    "relationship_saturation": {
      "new_relationships_count": "新关系数",
      "relationships_stability": "关系稳定性(0-1)",
      "network_completeness": "网络完整度(0-1)",
      "new_relationships": [
        {
          "id": "新关系ID",
          "from": "源概念/范畴ID",
          "to": "目标概念/范畴ID",
          "type": "关系类型",
          "significance": "重要性(0-1)"
        }
      ]
    },
    "theory_saturation": {
      "explanation_coverage": "解释覆盖度(0-1)",
      "internal_consistency": "内部一致性(0-1)",
      "phenomena_explained_count": "解释现象数",
      "theory_maturity": "理论成熟度(0-1)"
    },
    "statistical_analysis": {
      "confidence_interval": "置信区间",
      "statistical_significance": "统计显著性",
      "sample_size": "样本量",
      "effect_size": "效应量"
    }
  },
  "recommendations": {
    "continue_data_collection": "是否继续收集数据(true/false)",
    "focus_areas": ["需要关注的领域列表"],
    "next_steps": ["下一步建议列表"],
    "data_collection_strategy": "数据收集策略建议"
  },
  "metadata": {
    "timestamp": "时间戳",
    "version": "版本号",
    "skill": "checking-theory-saturation",
    "analysis_method": "分析方法"
  }
}

核心流程

第一步：概念饱和评估

1. 新概念识别：分析新数据中是否出现新概念
2. 概念重要性评估：评估新概念对理论的贡献
3. 概念抽象层次检查：验证概念抽象层次适当性
4. 概念频率统计：计算新概念出现频率

第二步：范畴饱和评估

1. 属性完整性检查：评估范畴属性发展充分性
2. 维度完整性检查：评估范畴维度覆盖全面性
3. 范畴间关系稳定性：检查范畴关系是否稳定
4. 范畴定义清晰度：验证范畴边界清晰性

第三步：关系饱和评估

1. 新关系识别：检查是否出现新概念关系
2. 关系稳定性：验证现有关系是否稳定
3. 关系强度评估：评估关系强度合理性
4. 关系网络完整性：检查关系网络覆盖完整性

第四步：理论饱和评估

1. 解释覆盖度：验证理论解释现象的全面性
2. 理论一致性：检查理论内部逻辑一致性
3. 理论贡献度：评估理论的学术贡献
4. 理论适用性：验证理论的实践适用性

第五步：综合判断

1. 多维度证据整合：整合各层面饱和度证据
2. 饱和度信心评估：评估饱和度判断的信心水平
3. 后续步骤建议：提供是否继续收集数据的建议
4. 质量保证措施：实施饱和度验证措施

第六步：规划与进度管理

1. 使用planning-with-files初始化项目规划
2. 创建理论饱和度检验任务计划文档
3. 跟踪各评估阶段的进度和完成情况
4. 记录饱和度检验过程中的关键发现和洞察
5. 监控项目整体进度和里程碑达成情况

输出格式

{
  "summary": {
    "saturation_level": "fully_saturated|partially_saturated|not_saturated",
    "confidence_level": 0.85,
    "concepts_emerging_rate": 0.05,
    "categories_development_score": 0.92
  },
  "details": {
    "concept_saturation": {
      "new_concepts_recent": 2,
      "average_per_data_set": 0.3,
      "significance_level": "low"
    },
    "category_saturation": {
      "attributes_completeness": 0.88,
      "dimensions_coverage": 0.91,
      "relations_stability": 0.94
    },
    "theory_saturation": {
      "explanation_coverage": 0.95,
      "internal_consistency": 0.89,
      "phenomena_explained": 23
    }
  },
  "recommendations": {
    "continue_data_collection": false,
    "focus_areas": ["minor_refinements"],
    "next_steps": ["proceed_to_selective_coding"]
  }
}

质量标准

• 采用多维度饱和度评估方法
• 基于充分证据进行饱和度判断
• 考虑中国研究语境的特殊性
• 提供明确的后续步骤建议

深入学习

• 扎根理论方法论文献
• 理论饱和度评估指南
• 中国语境下的饱和度评估案例
• 质性研究质量评估资源

完成标志

完成理论饱和度检验后应产出：

1. 明确的饱和度判断结果
2. 详细的多维度评估报告
3. 基于证据的判断理由
4. 清晰的后续步骤建议

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此技能为扎根理论研究提供系统的理论饱和度检验方法，确保理论构建的科学性、完整性和可靠性。