five

Definire/ridefinire i ceti medi. Ipotesi e dibattiti maturati nell'Istituto internazionale per le classi medie tra l'inizio del Novecento e il secondo dopoguerra = Defining/redefining middle classes. Hypotheses and debates developed within the International Institute for Middle Classes between the beginning of the twentieth century and the second after-war|中产阶级研究数据集|国际会议数据集

收藏
Mendeley Data2024-01-31 更新2024-06-27 收录
中产阶级研究
国际会议
下载链接:
http://siba-ese.unisalento.it/index.php/h-ermes/article/view/23125/19367
下载链接
链接失效反馈
资源简介:
The International Institute of the Middle Classes was created in Stuttgart (with Brussels as operating headquarter) in 1903. It was mostly inspired by F. Le Play's ideas and the chair's German socialism, and its main aims were to define middle classes and protect them from the development of monopoly capitalism and from the great industrial concentration. This paper outlines the debate concerning the definition of middle classes, within the Institution, which covered a time span ranging from the first years of the twentieth century to the second after-war. Furthermore, this study underlines the importance of the international Congresses that were organized by the Institute in various European cities (e.g., Liege in 1905, Vienna in 1908, Munich in 1911, Paris in 1924, Rome in 1927, Prague in 1935 and Brussels in 1948). Those Congresses were crucial to foreground the themes and issues associated with middle classes in Europe, and they even succeeded in affecting the manners whereby various national States were established
创建时间:
2024-01-31
用户留言
有没有相关的论文或文献参考?
这个数据集是基于什么背景创建的?
数据集的作者是谁?
能帮我联系到这个数据集的作者吗?
这个数据集如何下载?
点击留言
数据主题
具身智能
数据集  4098个
机构  8个
大模型
数据集  439个
机构  10个
无人机
数据集  37个
机构  6个
指令微调
数据集  36个
机构  6个
蛋白质结构
数据集  50个
机构  8个
空间智能
数据集  21个
机构  5个
5,000+
优质数据集
54 个
任务类型
进入经典数据集
热门数据集

China Health and Nutrition Survey (CHNS)

China Health and Nutrition Survey(CHNS)是一项由美国北卡罗来纳大学人口中心与中国疾病预防控制中心营养与健康所合作开展的长期开放性队列研究项目,旨在评估国家和地方政府的健康、营养与家庭计划政策对人群健康和营养状况的影响,以及社会经济转型对居民健康行为和健康结果的作用。该调查覆盖中国15个省份和直辖市的约7200户家庭、超过30000名个体,采用多阶段随机抽样方法,收集了家庭、个体以及社区层面的详细数据,包括饮食、健康、经济和社会因素等信息。自2011年起,CHNS不断扩展,新增多个城市和省份,并持续完善纵向数据链接,为研究中国社会经济变化与健康营养的动态关系提供了重要的数据支持。

www.cpc.unc.edu 收录

yahoo-finance-data

该数据集包含从Yahoo! Finance、Nasdaq和U.S. Department of the Treasury获取的财务数据,旨在用于研究和教育目的。数据集包括公司详细信息、高管信息、财务指标、历史盈利、股票价格、股息事件、股票拆分、汇率和每日国债收益率等。每个数据集都有其来源、简要描述以及列出的列及其数据类型和描述。数据定期更新,并以Parquet格式提供,可通过DuckDB进行查询。

huggingface 收录

全国 1∶200 000 数字地质图(公开版)空间数据库

As the only one of its kind, China National Digital Geological Map (Public Version at 1∶200 000 scale) Spatial Database (CNDGM-PVSD) is based on China' s former nationwide measured results of regional geological survey at 1∶200 000 scale, and is also one of the nationwide basic geosciences spatial databases jointly accomplished by multiple organizations of China. Spatially, it embraces 1 163 geological map-sheets (at scale 1: 200 000) in both formats of MapGIS and ArcGIS, covering 72% of China's whole territory with a total data volume of 90 GB. Its main sources is from 1∶200 000 regional geological survey reports, geological maps, and mineral resources maps with an original time span from mid-1950s to early 1990s. Approved by the State's related agencies, it meets all the related technical qualification requirements and standards issued by China Geological Survey in data integrity, logic consistency, location acc racy, attribution fineness, and collation precision, and is hence of excellent and reliable quality. The CNDGM-PVSD is an important component of China' s national spatial database categories, serving as a spatial digital platform for the information construction of the State's national economy, and providing informationbackbones to the national and provincial economic planning, geohazard monitoring, geological survey, mineral resources exploration as well as macro decision-making.

DataCite Commons 收录

Tropicos

Tropicos是一个全球植物名称数据库,包含超过130万种植物的名称、分类信息、分布数据、图像和参考文献。该数据库由密苏里植物园维护,旨在为植物学家、生态学家和相关领域的研究人员提供全面的植物信息。

www.tropicos.org 收录

DIV2K

DIV2K数据集分为: 列车数据: 从800高清高分辨率图像开始,我们获得相应的低分辨率图像,并为2、3和4个降尺度因子提供高分辨率和低分辨率图像 验证数据: 100高清晰度高分辨率图像用于生成低分辨率对应图像,低分辨率从挑战开始提供,并用于参与者从验证服务器获得在线反馈; 当挑战的最后阶段开始时,高分辨率图像将被释放。 测试数据: 100多样的图像用于生成低分辨率的相应图像; 参与者将在最终评估阶段开始时收到低分辨率图像,并在挑战结束并确定获胜者后宣布结果。

OpenDataLab 收录