Labour Inspection Checklist Dataset

The dataset is intended to use for machine learning to promote United Nations' sustainable development goal 8, target 8: "Protect labour rights and promote safe and secure working environments for all workers, including migrant workers, in particular women migrants, and those in precarious employment". It consists of 63634 instances with past inspections conducted by NLIA between 01/01/2012 and 01/06/2019. Each instance in LICD is described via 575 features and two target variables. Each feature represents either organisational or financial information about the inspected organisation. The first target variable is an identifier for the checklist that were used to inspect the organisation. The variable can be used in a machine learning model to predict the optimal checklist for a specific target organisation. The second target variable denotes whether non-compliance was found at the inspection. The variable can be used to in a machine learning to predict non-compliance to working environment regulations among potential target organisations for inspections. The features, target variables and column names of the dataset have been translated from Norwegian to English.

本数据集旨在应用于机器学习，以促进联合国可持续发展目标8的第8项目标：“保护劳工权益，并为所有工人，特别是妇女移民和临时就业工人，营造安全稳定的工作环境”。该数据集包含63634个案例，由NLIA在2012年1月1日至2019年1月6日期间进行的既往检查构成。LICD中的每个案例均通过575个特征和两个目标变量进行描述。每个特征代表被检查组织的相关组织或财务信息。第一个目标变量是用于检查组织的清单标识符，该变量可用于机器学习模型中预测特定目标组织的最佳清单。第二个目标变量表示在检查中是否发现不合规情况。该变量可用于机器学习模型中预测潜在目标组织对工作环境法规的不合规性。数据集的特征、目标变量和列名已从挪威语翻译为英语。