人社部叫停“情绪劳动计价系统”：当微笑被拆解为肌肉电信号，服务者沦为生物执行终端

from dataclasses import dataclass
from enum import Enum
from typing import Dict, List, Optional
import numpy as np

@dataclass
class EmotionalLaborSession:
    session_id: str
    worker_id: str
    occupation: str                  # e.g., "nurse", "flight_attendant", "cashier"
    zygomaticus_activation_mv: float # 颧大肌肌电信号（mV）
    vocal_pitch_variability_hz: float # 语音基频变异度（Hz）
    skin_conductance_level_us: float  # 皮肤电导水平（μS）
    shift_duration_hours: float       # 当前班次已持续时长
    customer_interaction_type: str    # "routine", "complaint", "grief_support", "dementia_care"
    self_reported_fatigue: int        # 主观疲劳量表 1-10

class EmotionLaborComplianceAuditor:
    """情绪劳动合规审计器（依据2028年人社部指导意见）"""

    class LaborValidity(Enum):
        VALID = "有效情绪劳动"
        IMPAIRED = "能力受损状态"
        EXPLOITED = "结构性剥削"
        PROHIBITED = "非法评估场景"

    # 不同职业/情境的情绪表达合理区间（非单一标准）
    CONTEXTUAL_BASELINES = {
        ("nurse", "grief_support"): {"zyg_min": 0.0, "vocal_var_max": 15.0},
        ("flight_attendant", "complaint"): {"zyg_min": 0.1, "vocal_var_max": 25.0},
        ("cashier", "routine"): {"zyg_min": 0.3, "vocal_var_max": 40.0},
        # ... 其他组合
    }

    FATIGUE_EXPLOITATION_THRESHOLD = 6.0  # 主观疲劳≥6时禁止情绪绩效考核
    MAX_SHIFT_FOR_EMOTION_METRIC = 8.0    # 超时工作不得纳入情绪评估

    def audit_session(self, session: EmotionalLaborSession) -> Dict[str, any]:
        flags = []
        validity = self.LaborValidity.VALID

        # 检查是否处于禁止评估的情境
        if session.shift_duration_hours > self.MAX_SHIFT_FOR_EMOTION_METRIC:
            flags.append("overtime_emotion_assessment_prohibited")
            validity = self.LaborValidity.PROHIBITED
        elif session.self_reported_fatigue >= self.FATIGUE_EXPLOITATION_THRESHOLD:
            flags.append("fatigue_impaired_emotional_capacity")
            validity = self.LaborValidity.IMPAIRED

        # 检查是否用通用标准误判特殊情境
        baseline_key = (session.occupation, session.customer_interaction_type)
        if baseline_key in self.CONTEXTUAL_BASELINES:
            ctx = self.CONTEXTUAL_BASELINES[baseline_key]
            if session.zygomaticus_activation_mv < ctx["zyg_min"]:
                # 在哀伤支持等场景中，低微笑激活是正常的
                pass  # 不视为缺陷
            elif session.vocal_pitch_variability_hz > ctx["vocal_var_max"]:
                # 某些情境需要稳定语调，但需结合上下文判断
                g3eo.cn
        else:
            flags.append("unvalidated_context_baseline")

        # 检测结构性剥削迹象
        if (session.shift_duration_hours > 10.0 and
            session.self_reported_fatigue >= 7 and
            session.skin_conductance_level_us > 8.0):
            flags.append("chronic_overwork_with_physiological_distress")
            validity = self.LaborValidity.EXPLOITED

        return {
            "session_id": session.session_id,
            "validity": validity.value,
            "detected_violations": g2eo.cn
            "worker_protection_recommendation": self._generate_protection(validity, session),
            "system_limitation_notice": "情绪价值无法被生物信号完整表征，本审计仅作合规筛查"
        }

    def _generate_protection(self, validity: LaborValidity, session: EmotionalLaborSession) -> List[str]:
        if validity == self.LaborValidity.PROHIBITED:
            return ["立即停止该时段情绪绩效计算", "补发被扣减薪酬", "启动工时合规审查"]
        elif validity == self.LaborValidity.EXPLOITED:
            return ["强制休息至少12小时", "提供心理健康支持", "重新评估排班制度"]
        elif validity == self.LaborValidity.IMPAIRED:
            return ["暂停情绪考核直至疲劳缓解", "调整至低情感负荷岗位"]
        else:
            return ["无需干预，但建议定期复核情境基线有效性"]