GaiaLens People Data: real-time (refreshed daily), covers c.17,000 publicly traded companies, 20 year history

The GaiaLens system uses a combination of intelligent web crawlers and Machine Learning to engineer innovative proprietary features such as diversity metrics at scale and in real-time. Surveying public sources of company personnel records, we identify metrics such as board and management diversity. Matching this with compensation data from annual reports, we calculate gender and ethnicity pay gaps. This sounds simple but is incredibly challenging, especially at scale and in real-time for over 17,000 global companies. Here are the people metrics that we collect data for and their respective population percentages across our c.17,000 coverage (at the time of writing July 2022): - Independent Lead Director Flag: 97% - Independent Chairperson Flag: 97% - Percentage of Women on the Board: 100% - Percentage of Women Executives: 97% - Percentage of Independent Directors on Board: 97% - Woman CEO Flag: 95% - Woman Chairperson Flag: 85% - CEO Changes per FY: 78% - Percentage of Women in Management: 67% - Board Gender Pay Gap: 43% - Ethnic Diversity on the Board: 38% - Percentage of non-white executives: 37% - Management Gender Pay Gap: 24% - Ethnic Diversity within Management: 28% - Management Ethnicity Pay Gap: 14% - Board Non-White Pay Gap: 19% - CEO vs Employee Pay ratio: 78%

搜集汇总

背景与挑战

背景概述

该数据集通过智能网络爬虫和机器学习技术，实时收集并计算全球约17,000家上市公司的人员指标，涵盖20年历史。核心数据包括董事会与管理层多样性、性别与种族薪酬差距等多项指标，并提供了各指标的覆盖比例。