工伤预防管理风险综合评估数据

主要用于对单位（市县街道乡镇园区）工伤预防管理风险进行综合评估，通过对工伤预防工作所涉及的企业双重预防机制创建率、重大隐患数量、重大隐患整改率、一般事故数量、较大以上事故数量、安全投入平均比例、安全培训平均率、事故亡人数等风险评估核心指标数据标准化处理和算法加工，最终生成各单位工伤预防管理风险综合指数，并依据综合指数能实现对应的等级划分、赋色信息推送和预警信息提示，为管理部门和工伤预防涉及的企业安全管理综合效能提供有效的分析工具和工作手段。1.对单位各组数据进行Min-Max标准化：①对于“越大越好的数据”（双防率、隐患整改率、安全投入比例、培训率）：Xi=(X-Xmin)/(Xmax-Xmin)，其中X是原始数据、Xmin是数据中的最小值、Xmax是数据中的最大值；②对于“越小越好的数据”（隐患数量、一般事故数、较大以上事故数、事故亡人数）：Xi=(Xmax - X) / (Xmax - Xmin)),其中X是原始数据、Xmin是数据中的最小值、Xmax是数据中的最大值。
2.设置权重Weight_i：双重预防机制创建率0.1、重大隐患数量数量0.1、重大隐患整改率0.15、一般事故数0.15、较大以上事故数0.2、安全投入平均比例0.05、安全培训平均率0.05、事故亡人数0.2。
3.街道（乡镇）综合评估指数 = ∑（Score_i × Weight_i ） ，其中 i 从 1 到 n 。
4.设置评估等级，即红、橙、黄、蓝4色。系数≥0.7表示等级较低，标识蓝色；0.5≤系数＜0.7表示等级一般，标识黄色；0.3≤系数＜0.5表示等级较高，标识橙色；系数＜0.3表示等级高，标识红色，及时赋色码推送用户。

This dataset is primarily used for comprehensive risk assessment of work injury prevention management for entities including counties, cities, subdistricts, towns, townships, and industrial parks. Through standardized processing and algorithmic processing of core risk assessment indicator data related to work injury prevention work, including the enterprise dual prevention mechanism creation rate, number of major hidden dangers, rectification rate of major hidden dangers, number of general accidents, number of relatively serious and above-level accidents, average safety investment proportion, average safety training rate, and number of fatalities in accidents, a comprehensive work injury prevention management risk index is finally generated for each entity. Based on this comprehensive index, corresponding risk level classification, color-coded information push, and early warning information prompts can be implemented, providing effective analysis tools and working means for management departments and enterprises involved in work injury prevention to improve their comprehensive safety management efficiency.
1. Min-Max standardization is performed on the data of each entity group:
① For beneficial indicators with higher values being better (dual prevention mechanism creation rate, hidden danger rectification rate, safety investment proportion, training rate): $X_i = frac{X - X_{min}}{X_{max} - X_{min}}$, where $X$ is the original data, $X_{min}$ is the minimum value in the dataset, and $X_{max}$ is the maximum value in the dataset;
② For detrimental indicators with lower values being better (number of hidden dangers, number of general accidents, number of relatively serious and above-level accidents, number of fatalities in accidents): $X_i = frac{X_{max} - X}{X_{max} - X_{min}}$, where $X$ is the original data, $X_{min}$ is the minimum value in the dataset, and $X_{max}$ is the maximum value in the dataset.
2. Weight settings: Weight_i is assigned as follows: dual prevention mechanism creation rate 0.1, number of major hidden dangers 0.1, rectification rate of major hidden dangers 0.15, number of general accidents 0.15, number of relatively serious and above-level accidents 0.2, average safety investment proportion 0.05, average safety training rate 0.05, and number of fatalities in accidents 0.2.
3. Comprehensive assessment index for subdistricts (towns) = $sum_{i=1}^{n} (Score_i imes Weight_i)$, where $i$ ranges from 1 to $n$.
4. Four risk assessment levels with corresponding color codes are set: red, orange, yellow, and blue. The specific rules are as follows:
- Score ≥ 0.7 indicates a low risk level, marked blue;
- 0.5 ≤ Score < 0.7 indicates a moderate risk level, marked yellow;
- 0.3 ≤ Score < 0.5 indicates a relatively high risk level, marked orange;
- Score < 0.3 indicates an extremely high risk level, marked red, with color codes pushed to users in a timely manner.

搜集汇总

数据集介绍

特点

该数据集包含807条记录，每月更新，主要用于评估工伤预防管理风险，涵盖多个核心指标如双重预防机制创建率、重大隐患数量等，通过标准化处理和加权算法生成综合评估指数和等级划分，适用于管理部门和企业安全管理效能分析。