Multifaceted Disparities Associated with Translator Earnings: A Quantitative Study of Upwork Profiles  

作　　者：Tyler Horan 

机构地区：[1]Data Analytics and Computational Social Science Program,University of Massachusetts Amherst,Amherst,MA 01003,USA

出　　处：《Journal of Social Computing》2024年第1期88-100,共13页社会计算（英文）

摘　　要：This study aims to quantitatively explore the multifaceted determinants that influence earnings in the translation industry.Using a dataset comprising 45000 translator profiles,the study focusses on delineating disparities correlated with demographic variables such as age,gender,home country wealth,and language pairs.The study uses a random forest regression model to delineate the complex interaction between gender,the economic standing of a translator’s domicile country,age,and linguistic proficiency,as they relate to earnings.Our findings substantiate and,in many ways,extend existing qualitative and anecdotal evidence that has shaped the discourse in this sector.The rigorous empirical framework employed here can be replicated or adapted to study other sectors within the gig economy,thus contributing to a more comprehensive understanding of labour dynamics in the digital age.

关 键 词：translation online employment gig economy intercultural communication 

分 类 号：H315.9[语言文字—英语]