## 3 Conceptual Model
Sex ratio has also been included in prior studies [13; 14] with significant results, which relates to China's relatively high sex ratios, i.e., more males than females on a national basis, potentially affecting the size of the technology workforce and ICT usage. Two other variables added to this group are unique for digital divide studies on China, namely the Han population and the young child dependency ratio. The Han population as a percent of the total population is included because US digital divide studies, which examined independent ethnicity factors, found them to be significant determinants of digital usage [34; 40; 41]. We posit that the Han proportion is linked to higher usage, as the Han majority in China is known to have higher educational and economic levels. The young child dependency ratio is added because greater proportions of children in certain provinces can influence technology adoption, including, for instance, expansion in ICT use due to the presence of a relatively younger population. The child dependency ratio has been significant in studies of Japan [42] and the US [34; 43]. Economics. A variety of income factors have been associated with ICT use across varied geographies of China. In particular, residential income was a major correlate of online shopping in Chinese counties [14], and urban and rural residential income were important correlates of a digital divide for prefectures in China [3]. Another economic factor, export of goods, was the leading determinant of ICT availability and usability in China's provinces [18]. We argue that it influences ICT use through the exporting process by being linked to advanced ICT use in the global supply chain. Although unemployment has seldom been incorporated in digital inequality studies, it was included and shown to be inversely related to the proportion of internet users in a study of digital inequality in the UK [44]. Correspondingly, employment was a positive correlate for certain ICT variables in China in 2006 and 2009 [18]. We include unemployment, reasoning that unemployed persons tend to have lower work impetus to use information technology but may have a higher demand for personal communications. In China, the unemployment measure excludes unemployed workers without official state registration, and some people who are registered as unemployed may actually be working or out of the labor force [45]. Education. Educational attainment has long been established as an ICT determinant [26]. In a global study, secondary and tertiary education were significant determinants for a variety of ICT variables at the state and provincial levels in the US and India [25]. College education was shown to be significant in studies of ICT and internet variables at the county level in the US [32; 33; 34]. It has been influential in the Chinese provincial digital divide literature as well [3; 13; 14; 18]. Innovation. Innovation has infrequently been incorporated in the prior digital divide literature and rarely for China. For Japanese prefectures, innovation was a leading determinant of ICT use [42]. For China, it was identified as an important influence on early internet adoption [46]. Likewise, R&D for enterprises was a moderate influence on certain ICT factors for provinces in 2006 and 2009 [18]. However, in a study of China's city data in 2016-2017, innovation as measured based on R&D and patents granted was found not to be significant [3] A further justification for including innovation in the present model is the increasing prominence of innovation in the two most recent 5-year plans of the central Chinese government [47]. Knowledge Production. Production of knowledge in digital content is an essential aspect of ICT use, yet it is hard to directly measure consistently by province. In an earlier study, the number of printed books stood as a proxy variable for digital knowledge and was determined to be significant [18].