Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Design Example: Analyzing Capacity Contours for Flood Risk Assessment01:17

Design Example: Analyzing Capacity Contours for Flood Risk Assessment

164
Flood risk assessment involves careful planning and analysis to ensure the safety of communities near water retention structures. Capacity contours are a vital tool in this process, as they illustrate the potential spread of water at specific levels in a given area. In the context of building a bund across a small valley, these contours play a critical role in evaluating the safety of nearby residential areas.In this example, the bund is intended to store stormwater in the valley. The engineers...
164
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches01:23

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

218
Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
218
Design Example: Designing Water Slide01:18

Design Example: Designing Water Slide

400
When designing a water slide, controlling the speed of water flow is crucial for rider safety while maintaining an exciting experience. As water flows down the slide, gravity causes it to accelerate, with its speed at the bottom depending on the height from which it starts. The higher the slide, the more potential energy the water has at the top, which is converted into kinetic energy as it descends, increasing its speed.
Bernoulli's principle determines the water's velocity along the slide....
400
Bias01:22

Bias

6.5K
Bias refers to any tendency that prevents a question from being considered unprejudiced. In research, bias occurs when one outcome or answer is selected or encouraged over others in sampling or testing. Bias can occur during any research phase, including study design, data collection, analysis, and publication.
In statistics, a sampling bias is created when a sample is collected from a population, and some members of the population are not as likely to be chosen as others (remember, each member...
6.5K
Design Consideration01:22

Design Consideration

388
Designing a structure involves a series of considerations, primarily the material's ultimate strength, calculated through tests that measure changes under increased force until the material reaches its breaking point or limit. The ultimate load, where the material breaks, is divided by its original cross-sectional area, resulting in the ultimate normal stress or strength. The ultimate shearing stress is another significant factor taken into account.
The factor of safety is another key...
388
Random Sampling Method01:09

Random Sampling Method

13.3K
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. Data are the result of sampling from a 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. Among the various sampling methods used by...
13.3K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Identifying Key Questions and Challenges in Microchimerism Biology.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2025
Same author

Cancer Prevalence across Vertebrates.

Cancer discovery·2024
Same author

Shared fate was associated with sustained cooperation during the COVID-19 pandemic.

PloS one·2024
Same author

The future of evolutionary medicine: sparking innovation in biomedicine and public health.

Frontiers in science·2023
Same author

Status does not predict stress: Women in an egalitarian hunter-gatherer society.

Evolutionary human sciences·2023
Same author

Generosity among the Ik of Uganda.

Evolutionary human sciences·2023
Same journal

Stable intuition and the rise of deliberative prosociality in childhood.

Nature human behaviour·2026
Same journal

Two roads to prosociality.

Nature human behaviour·2026
Same journal

Bridging the divide in motor learning research.

Nature human behaviour·2026
Same journal

Many conferences lack clear information about disability access.

Nature human behaviour·2026
Same journal

An effort recalibration framework for digital media use and cognition.

Nature human behaviour·2026
Same journal

Interoception in self-harm and suicide: a scoping review and meta-analysis.

Nature human behaviour·2026
See all related articles

Related Experiment Video

Updated: Nov 4, 2025

An R-Based Landscape Validation of a Competing Risk Model
05:37

An R-Based Landscape Validation of a Competing Risk Model

Published on: September 16, 2022

2.3K

Design principles for risk-pooling systems.

Lee Cronk1, Athena Aktipis2

  • 1Department of Anthropology, Rutgers University, New Brunswick, NJ, USA. leecronk@rutgers.edu.

Nature Human Behaviour
|May 28, 2021
PubMed
Summary
This summary is machine-generated.

Risk pooling enhances community resilience during crises by ensuring unpredictable needs are met without obligation. Effective systems require consensus on needs, visible resources, and appropriate network scale.

More Related Videos

Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods
13:04

Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods

Published on: September 19, 2012

12.2K
Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
07:31

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

7.3K

Related Experiment Videos

Last Updated: Nov 4, 2025

An R-Based Landscape Validation of a Competing Risk Model
05:37

An R-Based Landscape Validation of a Competing Risk Model

Published on: September 16, 2022

2.3K
Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods
13:04

Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods

Published on: September 19, 2012

12.2K
Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
07:31

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

7.3K

Area of Science:

  • Social Sciences
  • Economics
  • Anthropology

Background:

  • Risk pooling is a crucial strategy for enhancing individual, household, and community resilience, particularly during times of crisis.
  • Understanding the principles and foundations of effective risk-pooling systems is essential for their successful implementation.

Purpose of the Study:

  • To identify and discuss the core principles that underpin effective risk-pooling systems.
  • To explore the cultural and evolutionary foundations of risk pooling.
  • To examine the vulnerabilities inherent in risk-pooling systems and their relationship with commercial insurance.

Main Methods:

  • The study synthesizes existing literature and theoretical frameworks on risk pooling.
  • It analyzes the key characteristics and principles of successful risk-sharing mechanisms.
  • Discussion includes cultural, evolutionary, and economic perspectives on cooperation and mutual aid.

Main Results:

  • Effective risk pooling relies on principles such as covering unpredictable needs, non-repayable aid, prioritizing self-need, consensus on needs, resource visibility, partner selection, and adequate network scale.
  • Cultural and evolutionary factors significantly shape the development and function of risk-pooling behaviors.
  • Vulnerabilities include potential for cheating, free-riding, and misaligned incentives, which can be mitigated by specific system designs.

Conclusions:

  • Risk-pooling systems, when designed according to established principles, significantly bolster resilience against unpredictable events.
  • The study highlights the interplay between social norms, evolutionary predispositions, and economic mechanisms in facilitating collective risk management.
  • Further research into the design and implementation of robust risk-pooling strategies, including their comparison with formal insurance markets, is warranted.