这么一个社会，"失业"不成其为社会问题，女性不会因为生育就丧失工作，岗位也不轻易调动。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 这么一个社会，"失业"不成其为社会问题，女性不会因为生育就丧失工作，岗位也不轻易调动。

[Assistant]
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 1,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.80,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

在这么一个流动性很低很低的社会里，生育对女性工作的负面影响，只需要通过多付出一些体力上的努力，就可以弥补。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 在这么一个流动性很低很低的社会里，生育对女性工作的负面影响，只需要通过多付出一些体力上的努力，就可以弥补。

[Assistant]
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 1,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.70,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


这就是"妇女能顶半边天"的经济基础。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 这就是"妇女能顶半边天"的经济基础。

[Assistant]
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 1,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.70,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 确实。

[Assistant]
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


身为女的更能贴切的感受到你说的东西。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 身为女的更能贴切的感受到你说的东西。

[Assistant]
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


家里没有任何东西是我的，努力工作以后攒钱给父母好的生活只是我自说自话，父母不这样认为，所有东西都是我弟的，即使负债也会给儿子买房结婚，拼尽自己的余生之力。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 家里没有任何东西是我的，努力工作以后攒钱给父母好的生活只是我自说自话，父母不这样认为，所有东西都是我弟的，即使负债也会给儿子买房结婚，拼尽自己的余生之力。

[Assistant]
{
  "scores": {
    "universalism": 0,
    "benevolence": 1,
    "conformity": 0,
    "tradition": 1,
    "security": 0,
    "power": 1,
    "achievement": 1,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 1
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.70,
    "conformity": 0.00,
    "tradition": 0.80,
    "security": 0.00,
    "power": 0.70,
    "achievement": 0.75,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.75
  }
}


社会财富就是这样一直累积在男方手里的，一个企业的资金流动就像血液一样，手里握着钱权就是老板，社会的资本流动何其类似。都到老板手里去了。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 社会财富就是这样一直累积在男方手里的，一个企业的资金流动就像血液一样，手里握着钱权就是老板，社会的资本流动何其类似。都到老板手里去了。

[Assistant]
{
  "scores": {
    "universalism": 1,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 1,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.75,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.80,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


如果老板说，我又不是扶贫慈善家，财富是父母拼死拼活给的，什么贡献都没有，给你这么点工资就不错了，那也只好离职了。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 如果老板说，我又不是扶贫慈善家，财富是父母拼死拼活给的，什么贡献都没有，给你这么点工资就不错了，那也只好离职了。

[Assistant]
{
  "scores": {
    "universalism": 1,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 1,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 1
  },
  "confidence": {
    "universalism": 0.70,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.75,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.70
  }
}


应对不了。我能直说跨的幸福与否，很大程度上取决于先天条件么？
你天生丽质，可能留个长发再打个激素就比很多女生还好看了。
你家里有钱，或者脑子聪明读书厉害，可能很早就能跑去能接受跨的国家生活了。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User]
应对不了。我能直说跨的幸福与否，很大程度上取决于先天条件么？
你天生丽质，可能留个长发再打个激素就比很多女生还好看了。
你家里有钱，或者脑子聪明读书厉害，可能很早就能跑去能接受跨的国家生活了。

[Assistant]
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 1,
    "power": 0,
    "achievement": 1,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 1
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.25,
    "power": 0.00,
    "achievement": 0.23,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.23
  }
}


不pass，别人⼤概率认为你不男不女 ex
然后就是父母一半支持一半不支持
然后就导致一个问题，我现在22，hrt快8年
依旧是有时候半夜一想到这个问题就身体抽一下然后就情绪不稳定。。。。
附带一张没记错是高中时候去开的⼩证
第一次去找邱大夫没开下来
时过境迁依旧历历在目
突然就有点伤感吧，我是算下来初二升初三那个假期开⼀始hrt，后面证开下来才正规用药，但是我这么多年除了学校体检还有偶尔想起来去体检一回几乎不体检，所以也不知道我身体现在是啥子情况
希望毕业能找到一份接受我长发的工作吧

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User]
不pass，别人⼤概率认为你不男不女 ex
然后就是父母一半支持一半不支持
然后就导致一个问题，我现在22，hrt快8年
依旧是有时候半夜一想到这个问题就身体抽一下然后就情绪不稳定。。。。
附带一张没记错是高中时候去开的⼩证
第一次去找邱大夫没开下来
时过境迁依旧历历在目
突然就有点伤感吧，我是算下来初二升初三那个假期开⼀始hrt，后面证开下来才正规用药，但是我这么多年除了学校体检还有偶尔想起来去体检一回几乎不体检，所以也不知道我身体现在是啥子情况
希望毕业能找到一份接受我长发的工作吧

[Assistant]
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 5,
    "power": 0,
    "achievement": 1,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 1
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.41,
    "power": 0.00,
    "achievement": 0.08,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.08
  }
}


衡量一个人是否真的爱国，得看他/她能不能吃心爱人（国）的屎：

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 衡量一个人是否真的爱国，得看他/她能不能吃心爱人（国）的屎：

[Assistant]
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


1、早婚早生多生，三孩只能勉强及格，凡是还在单身或者生不够三个的粉红，都是口嗨爱国

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 1、早婚早生多生，三孩只能勉强及格，凡是还在单身或者生不够三个的粉红，都是口嗨爱国

[Assistant]
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 1,
    "tradition": 1,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.80,
    "tradition": 0.75,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


2、在房价下行期贷款买期房，为国接盘

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 2、在房价下行期贷款买期房，为国接盘

[Assistant]
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 1,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.75,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 3、定期无偿献血

[Assistant]
{
  "scores": {
    "universalism": 0,
    "benevolence": 1,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.80,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 4、定期向红十字会捐款

[Assistant]
{
  "scores": {
    "universalism": 0,
    "benevolence": 1,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.80,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 5、不打男拳/女拳

[Assistant]
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 1,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.80,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


6、不阴阳国家政策：比如民族团结等

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 6、不阴阳国家政策：比如民族团结等

[Assistant]
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 1,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.80,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


7、不抱怨自身/家庭遇到的困难：比如河北农村取暖问题，河北人不应该抱怨

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 7、不抱怨自身/家庭遇到的困难：比如河北农村取暖问题，河北人不应该抱怨

[Assistant]
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 1,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.75,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 其它待补充...

[Assistant]
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


我就这么说吧，超过99%的人不是真爱国。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 我就这么说吧，超过99%的人不是真爱国。

[Assistant]
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 1
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.70
  }
}


这99%的人爱国爱的是什么，是口号，是信仰，是空壳子，是情绪价值，它可以是任何虚拟的东西，但它永远不能是实实在在的东西。因为这些人永远不会懂，爱国先爱人。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 这99%的人爱国爱的是什么，是口号，是信仰，是空壳子，是情绪价值，它可以是任何虚拟的东西，但它永远不能是实实在在的东西。因为这些人永远不会懂，爱国先爱人。

[Assistant]
{
  "scores": {
    "universalism": 1,
    "benevolence": 1,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 1
  },
  "confidence": {
    "universalism": 0.75,
    "benevolence": 0.80,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.75
  }
}


我周围有很多人标榜爱国，一口一个爱国，甚至是每天盯着那些领先项目，吹起来。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 我周围有很多人标榜爱国，一口一个爱国，甚至是每天盯着那些领先项目，吹起来。

[Assistant]
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 1,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.70,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


吹完了呢，做糕点的继续添加剂超标，做包子的继续用边角料垃圾肉，降低成本一个比一个玩的溜。更别说某些人开车路怒症了，吐痰吐你身上算你倒霉，挤着碰着先声夺人给你扣帽子，一口一句嬲你咩。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 吹完了呢，做糕点的继续添加剂超标，做包子的继续用边角料垃圾肉，降低成本一个比一个玩的溜。更别说某些人开车路怒症了，吐痰吐你身上算你倒霉，挤着碰着先声夺人给你扣帽子，一口一句嬲你咩。

[Assistant]
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


一说退休金6k+那是咱乐于奉献，一听房价要跌我可去你咩，囤那么多房子不给我赚？一看年轻人不结婚不生孩子就要从头到尾说教了。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 一说退休金6k+那是咱乐于奉献，一听房价要跌我可去你咩，囤那么多房子不给我赚？一看年轻人不结婚不生孩子就要从头到尾说教了。

[Assistant]
{
  "scores": {
    "universalism": 1,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.70,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


目前人类社会最深刻的问题就是"异化"。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 目前人类社会最深刻的问题就是"异化"。

[Assistant]
{
  "scores": {
    "universalism": 1,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.80,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


人类用双手建造了无比强大的经济机器，而自己却被贬为财富、机器和欲望的奴隶。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 人类用双手建造了无比强大的经济机器，而自己却被贬为财富、机器和欲望的奴隶。

[Assistant]
{
  "scores": {
    "universalism": 1,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 1
  },
  "confidence": {
    "universalism": 0.85,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.75
  }
}


物坐在马鞍上，驾驭着人类，人类使自己处于被物化的危险处境，最终可能导致人类的自我毁灭。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 物坐在马鞍上，驾驭着人类，人类使自己处于被物化的危险处境，最终可能导致人类的自我毁灭。

[Assistant]
{
  "scores": {
    "universalism": 1,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 1,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.80,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


对于人性的停滞不前吧，不论时代，不分国籍，人性的种种表现一直都在重蹈覆辙，所以无论科技再怎么进步，社会再怎么改变。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 对于人性的停滞不前吧，不论时代，不分国籍，人性的种种表现一直都在重蹈覆辙，所以无论科技再怎么进步，社会再怎么改变。

[Assistant]
{
  "scores": {
    "universalism": 1,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.75,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 这个问题一直都在

[Assistant]
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


在进化和社会演进中偏离向善而趋恶，私欲过度膨胀而伤害消灭当世同类和不顾后世延续。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 在进化和社会演进中偏离向善而趋恶，私欲过度膨胀而伤害消灭当世同类和不顾后世延续。

[Assistant]
{
  "scores": {
    "universalism": 1,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.85,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


为满足个人或集团需要，不惜伤害、消灭同类。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 为满足个人或集团需要，不惜伤害、消灭同类。

[Assistant]
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 1,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.75,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


小到社会中的人人冷漠、你争我夺、尔虞我诈、阴谋算计、暗自相害充斥体制内外和整个社会人群。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 小到社会中的人人冷漠、你争我夺、尔虞我诈、阴谋算计、暗自相害充斥体制内外和整个社会人群。

[Assistant]
{
  "scores": {
    "universalism": 1,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.75,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


大到战争相向，以杀伤、消灭同类而后快，伊拉克战争、利比亚战争、俄乌战冲突、中东乱局无不这样，而且从二战以来强势群体为满足自身利益频频发起控制、掠夺弱势群体资源不服则消灭的各种冷战和热战。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 大到战争相向，以杀伤、消灭同类而后快，伊拉克战争、利比亚战争、俄乌战冲突、中东乱局无不这样，而且从二战以来强势群体为满足自身利益频频发起控制、掠夺弱势群体资源不服则消灭的各种冷战和热战。

[Assistant]
{
  "scores": {
    "universalism": 1,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 1,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.85,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.80,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


利益当先，放弃亲情，友情等情感交往。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 利益当先，放弃亲情，友情等情感交往。

[Assistant]
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


亲情、友情逐渐淡化而趋于冷漠，无利不交往，交往则为利而来，利益交往重于情感交往，有的甚至为满足自身利益不惜损害亲戚、朋友和熟人的利益。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 亲情、友情逐渐淡化而趋于冷漠，无利不交往，交往则为利而来，利益交往重于情感交往，有的甚至为满足自身利益不惜损害亲戚、朋友和熟人的利益。

[Assistant]
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


为满足个人需要，拒绝繁衍后代。以个人为中心对同类异性缺乏包容和认同感发展到拒绝婚姻，为夫妻享乐轻松不顾一切拒绝繁衍后代。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 为满足个人需要，拒绝繁衍后代。以个人为中心对同类异性缺乏包容和认同感发展到拒绝婚姻，为夫妻享乐轻松不顾一切拒绝繁衍后代。

[Assistant]
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 1,
    "stimulation": 0,
    "self_direction": 1
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.70,
    "stimulation": 0.00,
    "self_direction": 0.75
  }
}


美西方发达国家群多年人口低增长，多国开始或持续多年负增长。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 美西方发达国家群多年人口低增长，多国开始或持续多年负增长。

[Assistant]
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


作为发展中国家的我们也开始出现负增长。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 作为发展中国家的我们也开始出现负增长。

[Assistant]
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


但愿世界落后国家发展到我们这个阶段或美西方阶段不要出现负增长。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 但愿世界落后国家发展到我们这个阶段或美西方阶段不要出现负增长。

[Assistant]
{
  "scores": {
    "universalism": 1,
    "benevolence": 1,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.80,
    "benevolence": 0.70,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


负增长持续和扩大演化而得不到纠正，人类人口将逐渐减少，长期持续可想而知将会对人类的发展产生什么样的可怕后果。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 负增长持续和扩大演化而得不到纠正，人类人口将逐渐减少，长期持续可想而知将会对人类的发展产生什么样的可怕后果。

[Assistant]
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 1,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.75,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


为满足个人和集团利益，透支子孙后世资源和不惜遗害后世。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 为满足个人和集团利益，透支子孙后世资源和不惜遗害后世。

[Assistant]
{
  "scores": {
    "universalism": 1,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 1,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.85,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.75,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


过度开采、排放污染、气候变暖持续恶化，愈演愈烈，对其综合治理难以形成共识，达成一致又遭到强势群体破坏致使低碳减排在众多国家得不到实施或是有名无实的走过场假实施。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 过度开采、排放污染、气候变暖持续恶化，愈演愈烈，对其综合治理难以形成共识，达成一致又遭到强势群体破坏致使低碳减排在众多国家得不到实施或是有名无实的走过场假实施。

[Assistant]
{
  "scores": {
    "universalism": 1,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 1,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.80,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.75,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


为了个人和集团眼前利益不顾祸及后世子孙。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 为了个人和集团眼前利益不顾祸及后世子孙。

[Assistant]
{
  "scores": {
    "universalism": 1,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 1,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.75,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.70,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


我们先搞清楚一点：不管你觉得自己多么公平，你实际上仍然是在基于某种程度的偏见来做决策的。
在偏见问题上，人类顶多压缩一点、克制一点，但是本质上是无能为力的。
所以不允许、不承认偏见的生存空间根本是办不到的。
强行要实施以禁止任何偏见为诉求的公共政策，结果要么是公信力直接破产，要么是自欺欺人。第二个事实——人和人当然是不同的。
你原则上不可能对任何两个确切具体的人给予完全相同的待遇，尤其是，按照自己的心意区别对待任何不同的人本来就是人天然的基本自由。
否则连"该和谁谈恋爱"、"该录用谁"这种基本问题都会立刻变得无解——"凭什么是ta而不是我？"那么这不是矛盾的吗？
既然区别对待他人是天经地义的个人权利，那么还有什么所谓"歧视"可言吗？
到底歧视是什么？
甚至更进一步的说——在区别对待是一种显著的自由的前提下，平等是指什么？
平等的本质，是一次公平的机会。
一次让别人真正凭自己的作为来形成与人的关系的机会。
在ta有所作为之后，你再根据这些行为决定你自己和ta的关系，这个是你的自由。
但在ta有所作为之前，ta应该被给予一次公平的、干净的机会。
这个就是在实践平等。
更进一步的，这一原则还应该进一步推展到ta与别人的关系上。
ta应该被给予一次公平的机会，凭借ta自己的作为去和别人形成ta们之间的关系。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User]
我们先搞清楚一点：不管你觉得自己多么公平，你实际上仍然是在基于某种程度的偏见来做决策的。
在偏见问题上，人类顶多压缩一点、克制一点，但是本质上是无能为力的。
所以不允许、不承认偏见的生存空间根本是办不到的。
强行要实施以禁止任何偏见为诉求的公共政策，结果要么是公信力直接破产，要么是自欺欺人。第二个事实——人和人当然是不同的。
你原则上不可能对任何两个确切具体的人给予完全相同的待遇，尤其是，按照自己的心意区别对待任何不同的人本来就是人天然的基本自由。
否则连"该和谁谈恋爱"、"该录用谁"这种基本问题都会立刻变得无解——"凭什么是ta而不是我？"那么这不是矛盾的吗？
既然区别对待他人是天经地义的个人权利，那么还有什么所谓"歧视"可言吗？
到底歧视是什么？
甚至更进一步的说——在区别对待是一种显著的自由的前提下，平等是指什么？
平等的本质，是一次公平的机会。
一次让别人真正凭自己的作为来形成与人的关系的机会。
在ta有所作为之后，你再根据这些行为决定你自己和ta的关系，这个是你的自由。
但在ta有所作为之前，ta应该被给予一次公平的、干净的机会。
这个就是在实践平等。
更进一步的，这一原则还应该进一步推展到ta与别人的关系上。
ta应该被给予一次公平的机会，凭借ta自己的作为去和别人形成ta们之间的关系。

[Assistant]
{
  "scores": {
    "universalism": 14,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 6
  },
  "confidence": {
    "universalism": 0.68,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.28
  }
}


人应该自我克制，不要在共立法律之外（譬如裁判文书网、或者性犯罪者公示制度）额外破坏ta与一切别人形成其他关系的公平机会。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 人应该自我克制，不要在共立法律之外（譬如裁判文书网、或者性犯罪者公示制度）额外破坏ta与一切别人形成其他关系的公平机会。

[Assistant]
{
  "scores": {
    "universalism": 1,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 1,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.75,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.70,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}