GCRI · 社会与人类发展
技术与社会凝聚力
社会凝聚力 is the trust, shared norms and ties that let people cooperate across differences. Technology can strengthen it by connecting people and improving services, or weaken it through polarisation, surveillance, exclusion and loss of shared information. This page sets out how technology affects trust and participation, how cohesion is measured, and what evidence serves the governments and civil society organisations concerned.
Technology and social cohesion: how the risk develops.
Trust, misinformation and public outcomes. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Networks connect and sort
Digital networks let people find others with shared interests, which can build communities and also sort people into like-minded groups.
Surveillance erodes trust
When people believe they are watched, they may withdraw from public participation, especially groups that have been targeted before.
Exclusion divides
People without access or skills are left out of digital public services and conversations, widening social gaps.
Institutions anchor trust
Trust in institutions shapes whether people follow authority guidance in crises and accept collective decisions they disagree with.
拉丁美洲和加勒比的人口与风险暴露。
Population density, night lights and land cover over Latin America and the Caribbean, from NASA GIBS. Each layer carries its own date.
交互式地图需要JavaScript;图层列表和来源见下文。
图层 3
本页的人口与暴露情况
关于本图层
- 证据
- 估计值
- 来源
- 世界网格化人口 v4.11(NASA SEDAC(哥伦比亚大学 CIESIN))
- 提供方
- NASA SEDAC(哥伦比亚大学 CIESIN)
- 许可协议
- CC BY 4.0
- 年份版本
- null;基于人口普查的估算,静态(2020)
- 处理结果
- 约 1 公里网格
- 不确定性
- 基于人口普查的 2020 年每平方公里人口估算,作为风险暴露背景展示;不是受任何危害影响的人数。
- 经由以下途径到达
- gibs.earthdata.nasa.gov,仅在您允许实时地图后访问
关于本图层
- 证据
- 观测
- 来源
- VIIRS Black Marble(VNP46A2)(NASA LAADS DAAC)
- 提供方
- NASA LAADS DAAC
- 许可协议
- NASA 开放数据
- 年份版本
- 每日;卫星辐射亮度,已校正月光和大气影响
- 构建时的最新内容
- 2026-10-12
- 处理结果
- 约 500 米网格
- 不确定性
- 所示日期的卫星夜间辐射亮度;灯光是用电和停电的替代指标,并非对供应或获得电力情况的测量。
- 经由以下途径到达
- gibs.earthdata.nasa.gov,仅在您允许实时地图后访问
关于本图层
- 证据
- 观测(持续云层仍会造成缺口)
- 来源
- VIIRS NOAA-20 Level 3,8 天(NASA LANCE)
- 提供方
- NASA LANCE
- 许可协议
- NASA 开放数据
- 年份版本
- 8 天;卫星 8 天合成;持续云层仍会造成缺口
- 构建时的最新内容
- 2026-09-14
- 处理结果
- 约 1 公里网格
- 不确定性
- 截至所示日期的 8 天内地表的卫星皮肤温度,是高温风险暴露指标;不是气温、热指数,也不是高温预警。
- 经由以下途径到达
- gibs.earthdata.nasa.gov,仅在您允许实时地图后访问
关于本图层
- 证据
- 观测
- 来源
- VIIRS NOAA-20 校正反射率(NASA LANCE)
- 提供方
- NASA LANCE
- 许可协议
- NASA 开放数据
- 年份版本
- 每日;卫星图像
- 构建时的最新内容
- 2026-10-14
- 处理结果
- 约 250 米网格
- 不确定性
- 卫星图像。卫星或模型栅格数据,按提供方发布的原样呈现。云层、条带缺口和反演误差会造成缺口和噪声;数值是指标,而非某地的测量值。
- 经由以下途径到达
- gibs.earthdata.nasa.gov,仅在您允许实时地图后访问
关于本图层
- 证据
- 模型生成(GIBS 发布的最新年份)
- 来源
- MODIS Terra 和 Aqua 土地覆盖(MCD12Q1)(NASA LP DAAC)
- 提供方
- NASA LP DAAC
- 许可协议
- NASA 开放数据
- 年份版本
- 每年;卫星分类;GIBS 发布的最新年份
- 构建时的最新内容
- 2024-01-01
- 处理结果
- 约 500 米网格
- 不确定性
- 所示年份的卫星土地覆盖类别,含农田;该分类存在已知误差,并非农场登记册。
- 经由以下途径到达
- gibs.earthdata.nasa.gov,仅在您允许实时地图后访问
关于本图层
- 证据
- 观测(云层造成缺口)
- 来源
- MODIS Terra EVI(NASA LANCE)
- 提供方
- NASA LANCE
- 许可协议
- NASA 开放数据
- 年份版本
- 每日;卫星指数;云层造成缺口
- 构建时的最新内容
- 2026-10-13
- 处理结果
- 约 250 米网格
- 不确定性
- 截至所示日期 8 天的卫星植被指数,是栖息地状况指标;不衡量物种或生物多样性。
- 经由以下途径到达
- gibs.earthdata.nasa.gov,仅在您允许实时地图后访问
键盘操作,地图获得焦点时
按住 Ctrl 或 ⌘ 并滚动以缩放
最新可用
NASA GIBS / EOSDIS · ASTER GDEM (METI, NASA) · Blue Marble (NASA) · © OpenStreetMap贡献者 (ODbL) · Natural Earth
正在加载最新的NASA影像。
拖动以移动。按住 Ctrl 或 ⌘ 并滚动、双指缩放或使用按钮缩放;悬停可查看指针下的数值;重置可返回该区域。
人口与风险暴露,以拉丁美洲和加勒比地区为取景。NASA 发布的卫星和模型产品,各带自己的日期。它们是指标,而非对任何地点的评估。
数据:NASA GIBS · ASTER GDEM · Blue Marble · © OpenStreetMap 贡献者 · Natural Earth · NASA EONET · NASA JPL OPERA DIST-ALERT来源与许可
- We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA 开放数据
- We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA 开放数据
- Center for International Earth Science Information Network (CIESIN), Columbia University. 2018. Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11. NASA Socioeconomic Data and Applications Center (SEDAC). 采用 CC BY 4.0 许可。颜色依据已发布的色标重绘;显示处的数值已按六边形网格平均(经修改)。 doi:10.7927/H49C6VHW. CC BY 4.0
- VIIRS Black Marble 夜间灯光,NASA 戈达德航天中心;由 NASA Level-1 与大气档案和分发系统(LAADS DAAC)分发;影像来自 NASA GIBS。颜色依据已发布的色标重绘;显示处的数值已按六边形网格平均(经修改)。 NASA 开放数据
- VIIRS 近实时产品(洪水、地表温度、积雪覆盖、校正反射率),NASA LANCE;影像来自 NASA GIBS。颜色依据已发布的色标重绘;显示处的数值已按六边形网格平均(经修改)。 NASA 开放数据
- MODIS 陆地产品(植被指数、总初级生产力、土地覆盖),NASA LP DAAC 和 LANCE;影像来自 NASA GIBS。颜色依据已发布的色标重绘;显示处的数值已按六边形网格平均(经修改)。 NASA 开放数据
- ASTER GDEM 是 METI 和 NASA 的产品(ASTER Global Digital Elevation Model V003,NASA LP DAAC);影像来自 NASA GIBS。颜色依据已发布的色标重绘;显示处的数值已按六边形网格平均(经修改)。引用格式:NASA/METI/AIST/Japan Spacesystems and U.S./Japan ASTER Science Team (2019). ASTER Global Digital Elevation Model V003. doi:10.5067/ASTER/ASTGTM.003. NASA 开放数据
- 使用 Natural Earth 制作。免费矢量和栅格地图数据,见 naturalearthdata.com。 公有领域
- © OpenStreetMap 贡献者(ODbL),经由 NASA GIBS(海岸线、边界、道路和地名)。颜色依据已发布的色标重绘;显示处的数值已按六边形网格平均(经修改)。 ODbL
- Blue Marble,NASA Earth Observatory;影像来自 NASA GIBS。颜色依据已发布的色标重绘;显示处的数值已按六边形网格平均(经修改)。 NASA 开放数据
- 地球仪和平面地图上的背景信息:海岸线、边界、道路和地名来自 NASA GIBS 参考图层(OpenStreetMap 数据,ODbL,© OpenStreetMap contributors);Blue Marble 影像可作为可选底图;3D 地形和高程读数来自 ASTER GDEM 高程色彩指数(5 m 至 200 m 分级,为便于辨识而作了夸张处理)。边界按已发布的样式绘制,不代表对任何领土的立场。
- 实时事件:NASA Earth Observatory Natural Event Tracker(EONET);事件仅供参考,并保留其原始来源链接。
- 实时:NASA EONET。事件仅供参考,不是主管机构的预警。
- Observed (EO): NASA JPL OPERA DIST-ALERT (contains modified Copernicus Sentinel data 2026). We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS).
- NASA GIBS: We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS).
- 空气质量预报,5 天,PM2.5(CAMS,经由 Open-Meteo):包含经修改的 Copernicus 大气监测服务 2026 年信息。
- 天气数据来自 Open-Meteo.com (https://open-meteo.com/), 依据 CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). 授权。
- 可选图层(图层列表中有 9 个来源:实时、预报、观测和背景)开启时会在地图上和此处显示其提供方署名;预报是模型输出,派生指数是估计值。
图层与日期
- 人口密度,2020 年:人口:哥伦比亚大学 CIESIN,世界网格化人口 v4.11(2018),NASA SEDAC, CC BY 4.0 · 静态
- 夜间灯光,每日:VIIRS Black Marble(VNP46A2),NASA LAADS DAAC · 2026年10月12日
- 地表温度,日间,8 天合成:VIIRS NOAA-20 3 级产品,8 天,NASA LANCE · 2026年9月14日
- 真彩色:VIIRS NOAA-20 校正反射率,NASA LANCE · 2026年10月13日
- 土地覆盖类型(IGBP),年度:MODIS Terra 和 Aqua 土地覆盖(MCD12Q1),NASA LP DAAC · 2024
- 增强型植被指数,滚动 8 天:MODIS Terra EVI,NASA LANCE · 2026年10月13日
集体行为的阈值模型。
Each agent acts once enough of its contacts have; small changes in the mean threshold or the early movers decide whether the behaviour stays local or cascades through the population. Teaching model with stated illustrative values, not a prediction. The map on this page shows Latin America and the Caribbean; the model itself is not tied to a place.
控制措施
- 平均阈值(邻居比例)
- 18%
- 阈值的离散度
- 8 分
- 早期行动者
- 2.0% 的人口
- 人均接触数
- 8
读数
- 说明最终是谁采取了行动
- 100%
- 全球级联
- 是
- 结算步数
- 13
数字、方法与来源
| 步骤 | 已采取行动的比例(%) |
|---|---|
| 0 | 0.8 |
| 1 | 3.5 |
| 2 | 11.0 |
| 3 | 22.5 |
| 4 | 39.0 |
| 5 | 54.5 |
| 6 | 68.8 |
| 7 | 81.0 |
| 8 | 90.5 |
| 9 | 95.5 |
| 10 | 97.8 |
| 11 | 99.5 |
| 12 | 100.0 |
| 13 | 100.0 |
方法
- 集体行为的阈值模型 Granovetter(1978),American Journal of Sociology 83
- 随机网络上的全局级联 Watts (2002), PNAS 99
- 复杂传染 Centola and Macy (2007), American Journal of Sociology 113
- 单因素敏感性(龙卷风图) Saltelli and others (2008), Global Sensitivity Analysis: The Primer, Wiley
数据
No observed data enters this model: it runs on the teaching values set by the controls, to be replaced with a programme’s own evidence.
贯穿六大支柱,由 Nexus Consortium 牵头
- 实验 实验室
- 构建于 Foundry 中的社会与人类发展
- 检验地点 Universe 中的社会与人类发展
- 编入 Standards 中的治理、安全与社会
- 发表于 Reports 中的社会与人类发展
- 授课于 Academy 中的健康与社会学院
衡量什么,以及衡量得如何。
每个指标都注明其单位、频率、背后的来源类型以及数值将附带的证据标签。此处不显示数值:数值由计划依据其自身权限提供。
| 指标 | 单位 | 节奏 | 来源类型 | 标签 |
|---|---|---|---|---|
| Generalised trust | percent agreeing most people can be trusted | per survey | Values surveys | 已报告 |
| Trust in government | percent expressing confidence | per survey | Trust surveys | 已报告 |
| Affective polarisation | difference in feelings toward own and other groups | per survey | Election and social surveys | 已报告 |
| Civic participation | percent participating in community activities | per survey | Social surveys | 已报告 |
| Internet shutdowns | count of incidents | 年度 | Shutdown trackers | 已报告 |
| Digital public service use by group | percent of population | per survey | Household surveys | 已报告 |
Model technology and social cohesion as a system. Run the cascade.
Assembled from the Nexus Standards area profile 社会与信息风险标准: the hazards it names, the 系统 and sectors that carry the loss, the controls that dampen it and the data that observe it. Choose the components, pick an initiating hazard and step through the cascade. The Map view places the run on an example geography with open data. Every coupling weight is a stated assumption you can change. A teaching model, not a forecast, an assessment or a certification. To model a place of your own choosing, open the full System Builder.
灾害
- Civil unrest
- Supply-chain disruption (在下游引发)
- Currency crisis (在下游引发)
控制措施
NS-0章程与原则NS-9情境 UNI(部署、实例、计划实例)NS-11验证与监测(证据、证明、零信任符合性观测)NS-12软件、模型和 AI/ML 制品(供应链、模型卡、数据集说明)NRS-H117危害类别:社会凝聚力与暴行风险(NHS-1 soc.cohesion)NRS-X7信息完整性与公众信任NRS-D2社会、包容与人类发展风险NRS-H52危害类别:信息完整性攻击(NHS-1 cyber.integrity)NRS-H79危害类别:精神卫生危机(NHS-1 health.mental)NRS-H59危害类别:经济冲击与治理失灵(NHS-1 soc.economic)
观测
- WorldPop gridded population (listed for reference)
- World Bank Open Data 和 World Development Indicators API(仅列作参考)
- 全球可持续发展目标指标数据库(仅列作参考)
- 每100,000人中因灾害死亡、失踪和直接受影响的人数
- Proportion of people living below 50 per cent of median income
- Number of countries that adopt and implement guarantees for public access to information
示例地理范围
- The Horn of Africa: 253 hexagonal cells
- 今夜夜间灯光与停电(VIIRS 昼夜波段),NASA GIBS
证据来自何处。
具名公共数据集与机构记录,各自注明许可类别。依协议获得的来源仅按其条款使用,绝不再次发布。
| 来源 | 它提供什么 | 许可类别 |
|---|---|---|
| World Values Survey | Trust, values and participation across countries | Free for non-commercial use, terms to check |
| OECD Survey on Drivers of Trust in Public Institutions | Trust in government and its drivers | Public, OECD terms |
| Access Now KeepItOn shutdown data | Internet shutdown incidents | Public, terms to check |
| Afrobarometer, Latinobarómetro and other regional barometers | Public opinion on trust and governance | Free for non-commercial use, terms per survey |
| Pew Research Center global surveys | Attitudes toward technology and institutions | Public, terms per release |
How technology and social cohesion is modelled, measured and tested.
模型、其假设、数据和不确定性,以科学家或工程师会核查的形式呈现。结构遵循已发表的方法。所取数值仅为示意,不是研究发现。
系统模型
The couplings between the systems in technology and social cohesion: signs of influence, a reinforcing and a balancing loop, and cross-links where stress jumps.
由谁决定,以及证据服务于什么。
Society and Human Development prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.
| 谁来决定 | 问题 | 本页面服务的证据 |
|---|---|---|
| 政府 | How to design digital services and policies that build trust | Inclusion reviews; trust evidence |
| Civil society organisations | Where to focus on participation and inclusion | Participation and cohesion evidence |
| 监管机构 | How to address online harms without restricting rights | Studies of technology effects |
该主题产生的产出
- Trust and cohesion profiles
- Studies of technology effects on participation
- Inclusion reviews of digital public services
- Evidence notes for 社会凝聚力 strategies
专家提出的问题。
- How does trust in institutions affect compliance with public health or evacuation advice?
- How does misinformation spread, and what reduces its effects?
- Who is excluded by digital-only services, and with what consequences?
- How do online networks affect polarisation and 社会凝聚力?
- How does automated decision-making affect fairness in public services?
Trust, information and exclusion.
Trust shapes behaviour. During epidemics and disasters, people are more likely to follow guidance from sources they trust, and trust is built or lost by how institutions act over time. Misinformation spreads through social networks, often faster than corrections, especially when it is emotionally charged or aligned with existing beliefs. Prebunking, accurate and timely information from trusted messengers and community engagement are among the approaches with supporting evidence.
Digital exclusion follows lines of age, income, disability, gender and geography. When services move online, people without connectivity, devices, skills or digital identity can lose access to benefits and information. Algorithmic 系统 used in public services can reproduce bias in their training data. Cohesion is also affected by perceived fairness: crises that appear to burden some groups unfairly erode solidarity.
Design choices matter. Services that keep offline and assisted channels, explain automated decisions and allow appeal tend to preserve trust and inclusion, while opaque systems that cannot be challenged erode both, even when they are efficient on average.
Methods and limits.
Trust and attitudes
Surveys track trust, beliefs and behaviour; responses can differ from actions.
Information diffusion
Analysis of how content spreads on platforms; access to platform data is restricted.
Interventions
Field and online experiments test messaging and correction; effects can fade.
Limits: platform data access is uneven and changing, causal effects of exposure to misinformation are hard to isolate, and findings from one country or platform may not transfer.
Where this page’s references lead.
阅读本页时所对照的机构和文件。状态和版本会变化;每个链接都指向发布机构。
问题与解答。
What is social cohesion?
Does social media cause polarisation?
Why does trust matter in a crisis?
Does the platform fact-check content?
Is technology good or bad for cohesion?
Does the platform study specific platforms?
从本页贡献证据。
报告 is the Consortium’s quarterly publication. What you know about this subject can become evidence, a case or a correction in the next edition, credited to you and published under CC BY 4.0 where it is your own work.
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