技能型社会建设中的"社会":制度系统的支持之径
Society in the Construction of a Skill-based Society:Pathways of Institutional Support
杜连森1
作者信息
- 1. 江苏师范大学教育科学院,江苏徐州 221116
- 折叠
摘要
从世界主要工业国家的发展历程来看,在技能与社会系统的互动模式上大致存在两种类型的社会,一是以美国和英国为代表的技能抑制型社会,二是以日本和德国为代表的技能友好型社会.技能抑制型社会在工业生产逻辑上采取去技能化路径,其形成的市场条件为大规模统一市场,在劳资关系上呈现高对抗特点,在意识形态上秉持自由主义.技能友好型社会在工业生产上坚持技能依赖路径,其面向的市场为个性化高端市场,劳资关系较为缓和、协调,社会意识形态更偏向于平等主义.综合两类生产模式的经验和教训,我国的技能型社会建设在制度和政策方面可以采取如下策略:提高工人社会地位,加强劳动者权益保护;形成劳资利益共同体,建立稳定的雇佣制度;谨慎推行"机器换人",增强人机技能适配;避免大规模市场陷阱,推动市场需求高端化.
Abstract
From the development trajectories of major industrialized countries,there are generally two types of societies in terms of the interaction between skills and social systems.The first is skill-suppressing societies represented by the United States and the United Kingdom,while the second is skill-friendly societies represented by Japan and Germany.Skill-suppressing societies adopt a path of skill devaluation in industrial production,characterized by a unified mass market,high adversarial labor relations,and a liberal ideology.Skill-friendly societies emphasize skill reliance in industrial production,target personalized high-end markets,exhibit more harmonious and coordinated labor relations,and lean towards egalitarianism in terms of ideological orientation.Drawing from the experiences and lessons of both models,the construction of a skill-based society in China can adopt the following strategies in terms of institutions and policies.First,elevating the social status of workers and enhancing protection of labor rights.Second,forming a community of shared interests between labor and capital and establishing stable employment systems.Third,cautiously implementing automation replacing humans to enhance the adaptability of human-machine skills.Fourth,avoiding the pitfalls of large-scale markets and promoting the high-endization of market demand.
关键词
技能型社会/技能抑制/技能友好/社会逻辑Key words
skill-based society/skill suppression/skill-friendly/social logic引用本文复制引用
基金项目
江苏省高校哲学社会科学研究重大项目(2020SJZDA111)
江苏省教育科学规划战略性与政策性重大招标课题(A/2022/c11)
出版年
2024
NETL
NSTL
万方数据