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A National Data Program for the Social Sciences: The General Social Survey and International Survey Programme

A National Data Program for the Social Sciences: The General Social Survey and International Survey Programme
社会科学国家数据计划:综合社会调查和国际调查计划
批准号:
1851332
负责人:
Michael davern
金额:
$822.23万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-08-15 至 2023-07-31

项目摘要

项目成果

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中文摘要
翻译
国家社会科学数据计划:一般社会调查(NDPSS)是一个社会指标,基础设施和数据传播计划。它有四个目标。它收集美国社会的数据,以监测和解释态度,行为和属性在总体和个人层面的趋势。它审查了社会的结构和功能,以及各种次级群体的作用。它提供了美国和其他国家之间的比较,以便从比较的角度看待美国社会,并发展人类社会的普遍性,跨国模型。它使学者、学生和其他人可以快速、免费地访问高质量的数据。这些目标是通过定期收集和分发一般社会调查及其在国际社会调查方案中的联合调查来实现的。自1972年以来,GSS和ISSP已被有效地收集,广泛分发,并由世界各地的社会科学家和其他人进行了广泛的分析。超过30,000份研究出版物使用了GSS/ISSP,它们为社会科学的各个领域做出了贡献。例如,他们通过审查代际转移和社会流动以及研究教育和知识方面的代际变化,加深了对群组效应的理解。它们监测了群体间关系、性别角色、家庭结构和价值观、公民自由以及全球化对民族特性的影响等方面的变化。GSS/ISSP数据还用于其他科学领域,如环境科学、纳米技术、极地科学、计算机/信息科学以及医学和健康。政府、非营利组织和大众媒体也广泛使用GSS/ISSP数据。在教育方面,有2 000多本教科书和教学手册使用GSS/ISSP,每年有数十万学生使用。2020年GSS和相关的ISSP轮次(2019-2021)将继续基本的NDPSS使命,平衡复制以衡量社会变革,同时在国际和专题模块以及后续研究中进行方法和实质性创新。计划从过去的调查和创新扩展。 它们是:1)用户“模块”竞赛,以征集新的调查项目,挖掘新兴的社会科学主题和NSF的优先事项; 2)扩展多层次,多来源(MLMS)数据,通过数据链接扩展NDPSS中的数据; 3)在调查现场使用自适应设计,以提高样本的代表性; 4)与美国国家选举研究(ANES)合作该奖项反映了NSF的法定使命,并被认为是值得支持的,使用基金会的知识价值和更广泛的影响审查标准进行评估。
英文摘要
The National Data Program for the Social Sciences: General Social Survey (NDPSS) is a social indicators, infrastructure, and data-diffusion program. It has four aims. It gathers data on American society to monitor and explain trends in attitudes, behaviors and attributes at both the aggregate and individual levels. It examines the structure and functioning of society in general and the role of various sub-groups. It provides comparisons between the United States and other nations in order to view American society in comparative perspective and to develop generalizable, cross-national models of human society. It makes high-quality data easily accessible to scholars, students, and others expeditiously and without charge. These aims are accomplished by the regular collection and distribution of the General Social Survey (GSS) and its allied surveys in the International Social Survey Program (ISSP). Since 1972, the GSS and ISSP have been efficiently collected, widely distributed, and extensively analyzed by social scientists and others around the world. Over 30,000 research publications have utilized the GSS/ISSP and they have contributed to every field in the social sciences. For example, they have advanced understanding of cohort effects by examining intergenerational transfers and social mobility and studying intergenerational changes in education and knowledge. They have monitored changes in intergroup relations, gender roles, family structure and values, civil liberties and the impact of globalization on national identity. GSS/ISSP data are used in other science fields, such as environmental science, nanotechnology, polar science, computer/information science, and medical science and health. The GSS/ISSP data are also used extensively by government, non-profit organizations, and the mass media. In education, over 2,000 textbooks and teaching manuals utilize the GSS/ISSP and it is used annually by hundreds of thousands students. The 2020 GSS and associated ISSP rounds (2019-2021) will continue the basic NDPSS mission, balancing replication to measure societal change with both methodological and substantive innovation in both the international and topical modules and follow-up studies. Extensions from past surveys and innovations are planned. They are: 1) a user "module" competition to solicit new survey items that tap emerging social science topics and NSF priorities; 2) an expansion of the multi-level, multi-source (MLMS) data to expand data in the NDPSS through data linkage; 3) using adaptive design during survey fielding to enhance sample representativeness; and 4) working with the American National Election Studies (ANES) team to engage in additional data production surrounding the 2020 Presidential Election.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
期刊论文(6)
专著(0)
科研奖励(0)
会议论文
DOI: 10.1177/1536867x221083900
发表时间: 2022-03-01
期刊: STATA JOURNAL
影响因子: 4.8
作者: [Freese, Jeremy, Johfre, Sasha]
通讯作者: Johfre, Sasha
DOI: 10.1177/0081175020982632
发表时间: 2021-01-01
期刊: SOCIOLOGICAL METHODOLOGY, VOL 51, ISSUE 2
影响因子: --
作者: [Johfre, Sasha Shen, Freese, Jeremy]
通讯作者: Freese, Jeremy
Tracking US Social Change over a Half-Century: The General Social Survey at Fifty
追踪美国半个世纪的社会变迁:五十岁的综合社会调查
DOI: --
发表时间: 2020
期刊: Annual review of sociology
影响因子: 10.5
作者: [Peter V. Marsden Tom W. Smith, Michael Hout]
通讯作者: Michael Hout
The International Social Survey Program Modules on Religion, 1991–2018
国际社会调查计划宗教模块,1991-2018
DOI: 10.1080/00207659.2021.1976471
发表时间: 2021
期刊: International Journal of Sociology
影响因子: 2.1
作者: [Tom W. Smith, B. Schapiro]
通讯作者: B. Schapiro
共 6 条
    GSS: General Social Survey Competition 2022/2024
    • 批准号:
      2049169
    • 项目类别:
      Continuing Grant
    • 资助金额:
      $1592.49万
    • 财政年份:
      2021
    • 负责人:
      Michael davern
    • 依托单位:
    国内基金
    海外基金
    Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
    Data-driven Recommendation System Construction of an Online Medical Platform Based on the Fusion of Information
    Development of a Linear Stochastic Model for Wind Field Reconstruction from Limited Measurement Data
    • 批准号:
      --
    • 项目类别:
      --
    • 资助金额:
      40万元
    • 批准年份:
      2020
    • 负责人:
      Vikrant Gupta
    • 依托单位:
    基于Linked Open Data的Web服务语义互操作关键技术
    • 批准号:
      61373035
    • 项目类别:
      面上项目
    • 资助金额:
      77.0万元
    • 批准年份:
      2013
    • 负责人:
      冯志勇
    • 依托单位: