Survey Data Collection Methods Collaboration: Securing the Future of Social Surveys
Survey Data Collection Methods Collaboration: Securing the Future of Social Surveys
批准号:
ES/X014150/1
负责人:
Peter Lynn
金额:
$304.55万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2023
资助国家:
英国
项目状态:
未结题
起止时间:
2023 至 --
中文摘要
点击翻译按钮获取中文摘要
英文摘要
The survey data collection community is facing severe challenges in implementing surveys using pre-pandemic approaches. There are knowledge gaps regarding the advantages and disadvantages of different data collection techniques and approaches such as push-to-web, knock-to-nudge and video-interviewing, and particularly in the mixed-mode context. And there is limited capacity both of skilled interviewers and of research professionals. Recent developments are leading to changes in commissioner requirements for face-to-face data collection as well as having implications for fieldwork costs and the role of interviewers. In several areas of survey methodology, the need for development of improved methods and the need to identify and communicate best practice is urgent.The Survey Data Collection Methods Collaboration (SDCMC) is a response to these challenges and aims to deliver a step change in approaches to collecting population survey data in the UK to ensure that it will remain possible to carry out high quality social surveys of the kinds required by the public and academic sectors to monitor and understand society, and to provide an evidence base for policy. It will do this primarily through a rigorous programme of research focused on ensuring large-scale social surveys in the UK can innovate and adapt in a changing environment and continue to deliver high quality and inclusive data. The primary aim of the programme of work is to assess the quality implications of the most important survey design choices relevant to future UK surveys and provide good practice guidance and practical training materials, while a secondary aim is to identify promising ways to improve the capacity and skillset of both interviewers and research professionals and take steps towards making those improvements. The SDCMC will generate a range of research and training outputs and will engage in a programme of dissemination and promotion activities. Outputs will have a strong practical orientation, consisting of good practice guidance for survey design, survey implementation, survey commissioners and survey data users, all backed up by rigorous and well-documented research and with a range of associated activities to ensure that the lessons are disseminated to all relevant stakeholders and, where appropriate, embedded in institutional practice in a timely manner. The project will also seek to enable a whole community dialogue and collaborative response to wider strategic challenges and issues, as well as incorporating a strong training and capacity building component. To realise the vision of the SDCMC will require leadership, commitment and active participation of a broad range of stakeholders including those who commission surveys, those who implement them, those who use survey data and those involved in research and development of survey methods. Constructive dialogue and collaboration will be crucial to the successful delivery of the ambitious range of activities and outputs that we envisage. We have assembled an experienced project team including academics and survey practitioners (39 people from 14 institutions), who are committed to the necessary constructive collaboration and we will engage a wider range of other stakeholders during the course of the grant to ensure that our outputs directly benefit a wide range of audiences. Impact will be achieved not only on survey research and survey practice but also on a broad range of disciplines within the social sciences and beyond which employ social survey data for analysis through raised awareness and knowledge of issues and opportunities.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
Survey Resources Network
-
批准号:ES/G034303/1
-
项目类别:Research Grant
-
资助金额:$115.86万
-
财政年份:2008
-
负责人:Peter Lynn
-
依托单位:
Understanding non-response and reducing non-response bias
-
批准号:ES/E024246/1
-
项目类别:Research Grant
-
资助金额:$29.45万
-
财政年份:2007
-
负责人:Peter Lynn
-
依托单位:
国内基金
海外基金
登录
查看更多内容
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
-
批准号:--
-
项目类别:合作创新研究团队
-
资助金额:--
-
批准年份:2024
-
负责人:姚韬
-
依托单位:
Data-driven Recommendation System Construction of an Online Medical Platform Based on the Fusion of Information
-
批准号:--
-
项目类别:外国青年学者研究基金项目
-
资助金额:--
-
批准年份:2024
-
负责人:江洋子
-
依托单位:
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:
Molecular Interaction Reconstruction of Rheumatoid Arthritis Therapies Using Clinical Data
-
批准号:31070748
-
项目类别:面上项目
-
资助金额:34.0万元
-
批准年份:2010
-
负责人:Christine Nardini
-
依托单位:
高维数据的函数型数据(functional data)分析方法
-
批准号:11001084
-
项目类别:青年科学基金项目
-
资助金额:16.0万元
-
批准年份:2010
-
负责人:周迎春
-
依托单位:
染色体复制负调控因子datA在细胞周期中的作用
-
批准号:31060015
-
项目类别:地区科学基金项目
-
资助金额:25.0万元
-
批准年份:2010
-
负责人:莫日根
-
依托单位:
Computational Methods for Analyzing Toponome Data
-
批准号:60601030
-
项目类别:青年科学基金项目
-
资助金额:17.0万元
-
批准年份:2006
-
负责人:Axel Mosig
-
依托单位: