AIGC产业蓬勃发展，但在繁荣背后，人工智能迈向全面自动化还面临着“最后一英里”的悖论——即在“数据”到“智能”的过渡中，仍需要大量人力劳动的加持。平台型媒体中面向内容生产与审核的数据标注工作，门槛低，从业者多且身份复杂，属于最新的劳动密集型行业，其服务的对象是“算法技术”本身。因此，有学者提出：平台型媒体中的信息标注工作是“幽灵劳动”的典型代表。本文以平台型媒体中从业的数据标注员群体为研究对象，采用问卷调查法在这一职业群体中获取数据，共计收集376个有效样本并展开分析，综合采用国内外已有研究的视角，使用结构方程模型等探究平台型媒体数据标注员雇佣关系感知、职业认同与员工满意度的影响关系，以及职业认同在其中起到的中介作用。研究发现：效率、公平能提高平台型媒体中数据标注员的职业认同和员工满意度；发言权对平台型媒体中数据标注员的职业认同和职业满意度无显著影响；平台型媒体数据标注员的职业认同能提高其员工满意度；公平、效率会影响职业认同，进而影响员工满意度。本研究的创新之处在于，率先关注这一新兴产业发展中特殊阶段的职业群体，在数字资本主义视阈下讨论新型劳工议题，站在劳动者的立场展开研究并提炼相关结论，为平台媒体数据标注劳动的管理、健康发展以及公共政策的制定等提供一定的实证数据和启发。

The AIGC industry is burgeoning, yet behind this growth lies the challenge of AI's "last mile" in transitioning from raw data to true intelligence, where considerable human labor remains essential. Data annotation in content production and review within platform-type media represents a nascent yet labor-intensive sector, targeting algorithmic outputs as its primary service. This study investigates the phenomenon of "ghost labor" through the lens of data taggers employed in these platforms. By surveying 376 participants, the research explores relationships between employment perception, career identity, and job satisfaction among media data taggers, employing structural equation modeling. Findings indicate that both efficiency and fairness significantly influence career recognition and satisfaction, serving as mediators. This research emphasizes the importance of professional identity in enhancing employee satisfaction and highlights the impact of workplace fairness and operational efficiency. By addressing these aspects, the study contributes empirical insights and offers guidance for the ongoing discourse on labor dynamics within digital capitalism, with implications for policy formulation and industry practices.