相关实验视频
Updated: May 13, 2025

06:10
Using Generative Art to Convey Past and Future Climate Transitions
Published on: March 31, 2023
820
介绍二战期间欧洲选举数据和集会档案 (AIEEDA)
Lea Kaftan1, Bruno Della Sala2, Olga Jerjomina2
1GESIS Leibniz Institute for the Social Sciences, 50667, Cologne, Germany. lea.kaftan@gesis.org.
Scientific data
|April 15, 2025
概括
两次世界大战之间的欧洲选举数据和集会档案 (AIEEDA) 提供了关于欧洲议会选举 (1919-1939) 的全面数据集. 该资源有助于社会科学家分析历史投票模式和当代政治现象.
科学领域:
- 政治科学 政治科学是指政治学.
- 历史社会学 历史社会学
- 量化历史 量化历史
背景情况:
- 两次世界大战期间的欧洲 (1919-1939年) 经历了重大的民主转型和政治调整.
- 现有的数据集往往缺乏多层次的细节性或对这一时期的全面党级信息.
- 了解历史选举行为对于将当代政治趋势置于背景下至关重要.
研究的目的:
- 介绍"两次世界大战间欧洲选举数据和集会档案" (AIEEDA),这是一个新的多层次数据集.
- 为研究人员提供有关两次世界大战期间欧洲民主国家的详细选举,政党和内数据.
- 促进在关键的历史时刻研究投票行为,政党政治和民主稳定.
主要方法:
- 汇编了来自25个欧洲民主国家的137个国家议会选举的选举结果.
- 包括401个政党和35个联盟的时间不变的意识形态和组织变量.
- 收集和验证分类的选区/市级数据为选定的国家,与国家结果相关联.
主要成果:
- AIEEDA包含137个国家议会选举的全面选举数据和详细的政党/联盟信息.
- 该数据集包括412个内的时间变化的内参与数据.
- 爱沙尼亚,爱尔兰,意大利,拉脱维亚,荷兰和南斯拉夫的分类选举数据,以及法国,德国和英国的链接表.
结论:
- 对于研究历史投票和政党政治的社会科学家来说,AIEEDA 是一个宝贵的资源.
- 该档案允许在历史背景下对理论进行样本外测试.
- 它通过历史分析为了解当代政治问题提供了基础,例如激进右翼政党的兴起.
相关概念视频
Archival Research
15.9K
Some researchers gain access to large amounts of data without interacting with a single research participant. Instead, they use existing records to answer various research questions. This type of research approach is known as archival research. Archival research relies on looking at past records or data sets to look for interesting patterns or relationships. For example, a researcher might access the academic records of all individuals who enrolled in college within the past ten years and...
15.9K
Econometric Views (EViews)
90
Econometric Views, often stylized as EViews, is a package that merges statistical analysis with econometric studies. It is designed to provide tools for time series analysis, forecasting, and econometric model simulation. The software originated from MicroTSP software and has evolved significantly since its inception in 1981. The history of EViews is marked by a continuous effort to enhance its computational speed and user interface. It was initially developed for large computing systems but...
90
Statistical Methods for Analyzing Epidemiological Data
239
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
239
Cross-Sectional Research
11.1K
In cross-sectional research, a researcher compares multiple segments of the population at the same time. If they were interested in people's dietary habits, the researcher might directly compare different groups of people by age. Instead of following a group of people for 20 years to see how their dietary habits changed from decade to decade, the researcher would study a group of 20-year-old individuals and compare them to a group of 30-year-old individuals and a group of 40-year-old...
11.1K
Stratified Sampling Method
11.6K
Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a stratified sample, divide the population into groups called strata and then take a...
To choose a stratified sample, divide the population into groups called strata and then take a...
11.6K
Measures of Central Tendency
15.6K
The "center" of a data set is also a way of describing location. The two most widely used measures of the "center" of the data are the mean (average) and the median. The words "mean" and "average" are often used interchangeably. The substitution of one word for the other is common practice. The technical term is "arithmetic mean" and "average" is technically a center location. However, in practice among non-statisticians,...
15.6K

