CMap:一个数据库,用于在24个部门绘制职位名称,部门专业化和晋升
Shehryar Subhani1,2, Shahan Ali Memon2,3, Bedoor AlShebli4
1Computer Science Program, Science Division, New York University Abu Dhabi, Abu Dhabi, United Arab Emirates.
Scientific data
|July 14, 2025
概括
一个新的数据集,职业地图 (CMap),标准化了数以百万计的职位名称,并确定了跨行业的晋升. 此资源有助于研究职业流动性,专业化和劳动力市场动态.
科学领域:
- 计算社会科学 计算社会科学
- 劳动经济学 劳动经济学
- 劳动社会学工作的社会学.
背景情况:
- 了解职业流动性和职业发展轨迹对于分析劳动力市场动态至关重要.
- 现有的数据集往往缺乏规模和细节,无法全面研究职位专业化和晋升模式.
研究的目的:
- 介绍职业地图 (CMap),这是一个大规模的数据集,旨在促进对职业专业化,部门集中和职业进步的研究.
- 提供一个标准化和结构化的资源,用于分析数以百万计的职位名称和已识别的晋升.
主要方法:
- 利用自然语言处理和大型语言模型将520万个职位标题标准化为123,000个独特的条目.
- 开发了一个专业化指数来量化职位职称的部门集中.
- 整合了来自美国,英国和全球背景的验证和推断的促销数据.
主要成果:
- 创建了一个涵盖24个行业的综合数据集 (CMap).
- 标准化了大量的职位名称,使得一致的分析成为可能.
- 识别和结构化超过93,000个晋升 (验证和推断).
结论:
- CMap为调查职位层次,跨部门流动性和职业进步中的不平等提供了坚实的基础.
- 该数据集支持研究教育,经验和机构因素如何影响职业成果.
- 为经济学家,社会学家和研究劳动力市场的计算社会科学家提供了宝贵的资源.
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