Utilising Big Data in the Practice of Torture Survivors' Rehabilitation
大数据在酷刑幸存者康复实践中的应用
基本信息
- 批准号:ES/M010422/1
- 负责人:
- 金额:$ 26.91万
- 依托单位:
- 依托单位国家:英国
- 项目类别:Research Grant
- 财政年份:2015
- 资助国家:英国
- 起止时间:2015 至 无数据
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Many third sector and charitable organisations routinely collect information on those using their service but often are not able to fully use this information to improve the service they offer. This is due to the way in which the information is collected and recorded which, while suitable for some purposes, does not enable easy interrogation of the data to fully understand how their service is being delivered and where it could be improved. There is also scope to link the data held by charities to other national and international data sources to provide an opportunity for a much deeper analysis and understanding. This project will explore the feasibility of carrying out these linkages while protecting the confidentiality and rights of the victims themselves.For this project a charity concerned with the rehabilitation of victims of torture, Freedom from Torture, has partnered with the University of Essex to explore how the data they collect and hold can be re-structured and cleaned to make it suitable for research and analysis. Freedom from Torture (FfT) is a national charity established in 1985 and has grown to have centres in London, Manchester, Glasgow, Birmingham and Newcastle and a service in Yorkshire and Humberside. They provide services to over 1,000 survivors of torture a year, who reside in the UK, most of whom are asylum seekers or have been granted some form of international protection. Their clients have experienced serious abuse and trauma and have complex needs and FfT prioritises helping those whose needs cannot be met by the National Health Service (NHS), social services or other voluntary sector organisations. FfT also provides other organisations that offer health and social care services with support for training, capacity building and promoting awareness of the unique needs of torture survivors. The work FfT carry out is informed by the experiences and voices of survivors of torture who access their services and FfT involve clients and former clients at every level through Service Users groups. FfT provides holistic care for each individual client and family following a comprehensive needs assessment. This approach embraces crisis intervention, long term rehabilitation, practical assistance, and / or the preparation of medico-legal reports which forensically document torture related injuries. Freedom from Torture's overall strategic aims are:(1) Rehabilitation: That survivors of torture in the UK realise their right to as full rehabilitation as possible; (2) Protection: Survivors of torture in the UK receive effective protection and are not returned to their countries of origin to face the risk of further torture; (3) Accountability: States responsible for torture are held to account publicly and the human rights of survivors are guaranteed nationally and internationally.With these aims in mind this project will also explore how the Freedom from Torture information can be linked with other external data sources such as geograhical information or international information on human rights. We will explore what data can be made available in anonymised form to users in the third sector, academic and social policy researchers while protecting the identity and confidentiality of the victims themselves. A major aim of the project is to provide a data infrastructure that will support the development of best practice in the delivery of cost-effective and successful social support and therapeutic treatments for victims of torture. The project will therefore feed into many policy debates about how services are delivered and the best practice standards that should be applied. Being a victim of torture is a traumatic and scarring event in people's lives and supporting their recovery and rehabilitation in the best way possible underlies the core activities of this project.
许多第三部门和慈善组织经常收集使用其服务的人的信息,但往往无法充分利用这些信息来改善其提供的服务。这是由于收集和记录信息的方式,这种方式虽然适用于某些目的,但不能方便地询问数据,以充分了解其服务是如何提供的,以及在哪里可以改进。还可以将慈善机构持有的数据与其他国家和国际数据来源联系起来,为更深入的分析和理解提供机会。该项目将探讨在保护受害者本身的机密性和权利的同时进行这些联系的可行性。在该项目中,一个关注酷刑受害者康复的慈善机构--免于酷刑--与埃塞克斯大学合作,探索如何重新组织和清理他们收集和持有的数据,使其适合研究和分析。免于酷刑自由(FFT)是一家全国性慈善机构,成立于1985年,现已在伦敦、曼彻斯特、格拉斯哥、伯明翰和纽卡斯尔设有中心,并在约克郡和亨伯赛德提供服务。他们每年为居住在英国的1000多名酷刑幸存者提供服务,他们中的大多数是寻求庇护者或已获得某种形式的国际保护。他们的客户经历了严重的虐待和创伤,有着复杂的需求,FFT优先帮助那些国家医疗服务(NHS)、社会服务或其他志愿部门组织无法满足需求的人。FFT还向提供保健和社会护理服务的其他组织提供支持,帮助培训、能力建设和提高对酷刑幸存者独特需求的认识。FFT开展的工作由获得其服务的酷刑幸存者的经历和声音提供信息,FFT通过服务用户组让各级客户和前客户参与进来。FFT在经过全面的需求评估后,为每个客户和家庭提供全面的护理。这一办法包括危机干预、长期康复、实际援助和/或编写法医法律报告,对与酷刑有关的伤害进行取证记录。免于酷刑的总体战略目标是:(1)康复:使英国的酷刑幸存者实现其尽可能全面康复的权利;(2)保护:英国的酷刑幸存者得到有效保护,不会被送回原籍国,面临进一步酷刑的风险;(3)问责:对酷刑负有责任的国家被公开追究责任,幸存者的人权得到国家和国际的保障。我们将探讨哪些数据可以匿名的形式提供给第三部门的用户、学术和社会政策研究人员,同时保护受害者本身的身份和机密性。该项目的一个主要目的是提供一个数据基础设施,支持制定最佳做法,为酷刑受害者提供具有成本效益和成功的社会支助和治疗。因此,该项目将成为许多关于如何提供服务和应采用的最佳做法标准的政策辩论的内容。成为酷刑受害者是人们生活中的一件创伤和伤痕累累的事件,以尽可能好的方式支持他们的康复和康复是该项目核心活动的基础。
项目成果
期刊论文数量(4)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Augmenting Co-Training With Recommendations to Classify Human Rights Violations
- DOI:10.1109/bigdata47090.2019.9005478
- 发表时间:2019-12
- 期刊:
- 影响因子:0
- 作者:Ragini Kihlman;Maria Fasli
- 通讯作者:Ragini Kihlman;Maria Fasli
Matrix factorization for co-training algorithm to classify human rights abuses In
用于对侵犯人权行为进行分类的协同训练算法的矩阵分解
- DOI:
- 发表时间:2018
- 期刊:
- 影响因子:0
- 作者:Gokhale R;
- 通讯作者:Gokhale R;
Deploying A Co-training Algorithm to Classify Human-Rights Abuses
部署协同训练算法对侵犯人权行为进行分类
- DOI:
- 发表时间:2017
- 期刊:
- 影响因子:0
- 作者:Gokhale, R.
- 通讯作者:Gokhale, R.
A Co-training algorithm to classify Human-Right Abuses
一种对侵犯人权行为进行分类的协同训练算法
- DOI:
- 发表时间:2017
- 期刊:
- 影响因子:0
- 作者:Gokhale, R.
- 通讯作者:Gokhale, R.
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
数据更新时间:{{ journalArticles.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ monograph.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ sciAawards.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ conferencePapers.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ patent.updateTime }}
Maria Fasli其他文献
Exploring Trading Strategies and their Effects in the FX Market
探索交易策略及其对外汇市场的影响
- DOI:
- 发表时间:
2016 - 期刊:
- 影响因子:0
- 作者:
M. Aloud;Maria Fasli - 通讯作者:
Maria Fasli
Exploring Trading Strategies and Their Effects in the Foreign Exchange Market
探索外汇市场的交易策略及其影响
- DOI:
10.1111/coin.12085 - 发表时间:
2017 - 期刊:
- 影响因子:2.8
- 作者:
M. Aloud;Maria Fasli - 通讯作者:
Maria Fasli
Formal Systems and Agent-Based Social Simulation Equals Null?
正式系统和基于代理的社会模拟等于零?
- DOI:
- 发表时间:
2004 - 期刊:
- 影响因子:0
- 作者:
Maria Fasli - 通讯作者:
Maria Fasli
e-Game: A platform for developing auction-based market simulations
电子游戏:开发基于拍卖的市场模拟的平台
- DOI:
- 发表时间:
2008 - 期刊:
- 影响因子:7.5
- 作者:
Maria Fasli;Michael Michalakopoulos - 通讯作者:
Michael Michalakopoulos
Stylized facts of trading activity in the high frequency FX market : An Empirical Study
高频外汇市场交易活动的典型事实:实证研究
- DOI:
- 发表时间:
2013 - 期刊:
- 影响因子:0
- 作者:
M. Aloud;Maria Fasli;E. Tsang;A. Dupuis;R. Olsen - 通讯作者:
R. Olsen
Maria Fasli的其他文献
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
{{ truncateString('Maria Fasli', 18)}}的其他基金
Business and Local Government Data Research Centre Legacy Status Proposal
企业和地方政府数据研究中心遗留状态提案
- 批准号:
ES/Y003411/1 - 财政年份:2024
- 资助金额:
$ 26.91万 - 项目类别:
Research Grant
Business and Local Government Data Research Centre
商业和地方政府数据研究中心
- 批准号:
ES/S007156/1 - 财政年份:2019
- 资助金额:
$ 26.91万 - 项目类别:
Research Grant
DADO - Data Analytics Driven by Ontologies
DADO - 由本体驱动的数据分析
- 批准号:
EP/M507702/1 - 财政年份:2014
- 资助金额:
$ 26.91万 - 项目类别:
Research Grant
Innovative tools to enable exploration of complex and specialised data sets
支持探索复杂且专业的数据集的创新工具
- 批准号:
EP/M507106/1 - 财政年份:2014
- 资助金额:
$ 26.91万 - 项目类别:
Research Grant
Smart Data Analytics for Business and Local Government
企业和地方政府的智能数据分析
- 批准号:
ES/L011859/1 - 财政年份:2014
- 资助金额:
$ 26.91万 - 项目类别:
Research Grant
相似国自然基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
- 批准号:
- 批准年份:2024
- 资助金额:万元
- 项目类别:合作创新研究团队
ARF鸟苷酸交换因子BIG1介导ACSL4依赖性铁死亡在非酒精性脂肪性肝炎中的作用及机制研究
- 批准号:
- 批准年份:2022
- 资助金额:30 万元
- 项目类别:青年科学基金项目
基于Big Code深度背景增强的Android应用代码反混淆研究
- 批准号:61972290
- 批准年份:2019
- 资助金额:60.0 万元
- 项目类别:面上项目
BIG1介导STING囊泡转运在抗肺癌免疫反应中的作用及分子机制
- 批准号:81903639
- 批准年份:2019
- 资助金额:21.0 万元
- 项目类别:青年科学基金项目
水稻Big Grain3 通过调控细胞分裂素转运调节籽粒大小
- 批准号:2019JJ50243
- 批准年份:2019
- 资助金额:0.0 万元
- 项目类别:省市级项目
ARF鸟苷酸交换因子BIG1调控巨噬细胞重编程在脓毒症免疫抑制形成中的作用及机制研究
- 批准号:81971488
- 批准年份:2019
- 资助金额:56.0 万元
- 项目类别:面上项目
控制豆科作物器官大小关键基因BIG SEEDS1的功能与应用研究
- 批准号:31771345
- 批准年份:2017
- 资助金额:65.0 万元
- 项目类别:面上项目
生长素转运调控基因BIG介导高浓度CO2下气孔关闭的分子机制
- 批准号:31171356
- 批准年份:2011
- 资助金额:65.0 万元
- 项目类别:面上项目
ARF鸟苷酸交换因子BIG1定向调控ABCA1功能的分子机制
- 批准号:81173056
- 批准年份:2011
- 资助金额:69.0 万元
- 项目类别:面上项目
BIG2介导的GABAA型受体转运模式及信号调控机制
- 批准号:31070924
- 批准年份:2010
- 资助金额:35.0 万元
- 项目类别:面上项目
相似海外基金
Conference: Theory and Foundations of Statistics in the Era of Big Data
会议:大数据时代的统计学理论与基础
- 批准号:
2403813 - 财政年份:2024
- 资助金额:
$ 26.91万 - 项目类别:
Standard Grant
FightAMR: Novel global One Health surveillance approach to fight AMR using Artificial Intelligence and big data mining
FightAMR:利用人工智能和大数据挖掘对抗 AMR 的新型全球统一健康监测方法
- 批准号:
MR/Y034422/1 - 财政年份:2024
- 资助金额:
$ 26.91万 - 项目类别:
Research Grant
Big mobile phone GPS data driven pseudo individual life-pattern generation
大手机GPS数据驱动伪个体生活模式生成
- 批准号:
24K17367 - 财政年份:2024
- 资助金额:
$ 26.91万 - 项目类别:
Grant-in-Aid for Early-Career Scientists
Exploring Hotel Customer Experiences in Japan via Big Data and Large Language Model Analysis
通过大数据和大语言模型分析探索日本酒店客户体验
- 批准号:
24K21025 - 财政年份:2024
- 资助金额:
$ 26.91万 - 项目类别:
Grant-in-Aid for Early-Career Scientists
Big Data-based Distributed Control using a Behavioural Systems Framework
使用行为系统框架的基于大数据的分布式控制
- 批准号:
DP240100300 - 财政年份:2024
- 资助金额:
$ 26.91万 - 项目类别:
Discovery Projects
CC* Networking Infrastructure: Enabling Big Science and Big Data Projects at the University of Massachusetts
CC* 网络基础设施:支持马萨诸塞大学的大科学和大数据项目
- 批准号:
2346286 - 财政年份:2024
- 资助金额:
$ 26.91万 - 项目类别:
Standard Grant
REU Site: Online Interdisciplinary Big Data Analytics in Science and Engineering
REU 网站:科学与工程领域的在线跨学科大数据分析
- 批准号:
2348755 - 财政年份:2024
- 资助金额:
$ 26.91万 - 项目类别:
Standard Grant
Market Orientation, Big Data Analysis Capability, and Business Performance: The Moderating Role of Supplier Relationship, Big data Analysis Outscoring
市场导向、大数据分析能力与经营绩效:供应商关系的调节作用、大数据分析得分
- 批准号:
24K05127 - 财政年份:2024
- 资助金额:
$ 26.91万 - 项目类别:
Grant-in-Aid for Scientific Research (C)
Generative Visual Pre-training on Unlabelled Big Data
未标记大数据的生成视觉预训练
- 批准号:
DP240101848 - 财政年份:2024
- 资助金额:
$ 26.91万 - 项目类别:
Discovery Projects
MEGASKILLS [MEthodology of Psycho-pedagogical, Big Data and Commercial Video GAmes procedures for the European SKILLS Agenda Implementation]
MEGASKILLS [欧洲技能议程实施的心理教育学、大数据和商业视频游戏程序的方法]
- 批准号:
10069843 - 财政年份:2023
- 资助金额:
$ 26.91万 - 项目类别:
EU-Funded