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Measuring Resilience.

Robert R Hoffman1, P A Hancock2

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Summary
This summary is machine-generated.

This study introduces a novel approach to measuring resilience capacity in human-machine systems. Validated measures are crucial for understanding complex emergent properties in macrocognitive system science.

Keywords:
adaptabilitymacrocognitive systemsmeasurement capacityresiliencesensemaking

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Area of Science:

  • Human Factors and Ergonomics (HF/E)
  • System Science
  • Macrocognition

Background:

  • Resilience is a key goal in technology and work system design, central to resilience engineering.
  • A systems approach to HF/E necessitates defining and measuring complex emergent properties like resilience.
  • This work addresses the need for a definitive specification and measurement methodology for resilience.

Purpose of the Study:

  • To promote discussion on measuring the complex phenomenon of resilience in human-machine systems.
  • To offer a quantifiable approach for assessing resilience capacity.
  • To provide a framework for comparing resilience across diverse systems and domains.

Main Methods:

  • Employed rational analytic and synthetic methods.
  • Developed a proposed approach for measuring resilience capacity.
  • Focused on creating a methodology for quantitative assessment.

Main Results:

  • Presented an approach to measure resilience capacity.
  • Demonstrated how the approach can compare resilience across multiple systems and domains.
  • Highlighted avenues for future development and validation of the proposed measures.

Conclusions:

  • Emerging concepts like resilience and adaptability are increasingly important.
  • Quantitative answers are needed to address skepticism regarding these dimensions.
  • Robust, validated resilience measures will facilitate rational discourse in macrocognitive system science.