In the 1960s, Sino-Soviet relation deteriorated sharply, the border war broke out between China and India, and the Vietnam War expanded into southern China. Faced with such a severe situation, China’s military industry, which was mainly distributed along the coastal border was very vulnerable to destruction. Under this background, a large number of industries especially military industries had moved to inland mountainous areas, at the same time, millions of workers, technical experts, cadres, and PLA officers and soldiers across the country had accept the police that required them to relocate from their original residences and gather in such factories since 1964. Until the end of the last century, the international situation had gradually eased and China began to reform and open up. These military-industrial units began to transform from state-owned to marketization. Companies that used to rely on state and national defense funds were facing multiple predicaments such as technology loss, aging population, and laid-off workers due to their geographical and economic location.
This work takes a military-industrial unit of the air force in central and southern China as a case. It presents the image as a reminiscence gesture, trying to explore how does this community face the private and individual life impacts brought by the change of times within the context of the “short and painful period” of market economic reform from the perspective of daily experience and emotional description. It pays particular attention to the more complex emotional conditions shown by female workers compared to the rapid adaptation to system of male workers under the whole political-economic background.
Chen Qiushi was born in Hunan, China. He obtained a dual bachelor’s degree in law/philosophy from Southeast University in 2015 and is currently studying in Glasgow school of Art MFA program. He uses image as the main medium for work and his art practice is deeply rooted in Chinese experience, aiming to explore photography, ethics, memory and relevant fields through a de-topic method.
