Book contents
- Negotiating Values
- Negotiating Values
- Copyright page
- Dedication
- Contents
- Figure and Tables
- Preface and Acknowledgments
- Abbreviations
- 1 Rare Opportunity
- 2 Origins of Continuous Distribution
- 3 Managing the Implementation of Organizational Change
- 4 Varieties of Expertise
- 5 Public (Community) Participation in Policymaking
- 6 Evidence and Values in Continuous Distribution Design
- 7 Organ Acceptance and Continuous Distribution
- 8 Constructed Collaboration
- Appendix
- References
- Index
4 - Varieties of Expertise
Published online by Cambridge University Press: 30 November 2025
Book contents
- Negotiating Values
- Negotiating Values
- Copyright page
- Dedication
- Contents
- Figure and Tables
- Preface and Acknowledgments
- Abbreviations
- 1 Rare Opportunity
- 2 Origins of Continuous Distribution
- 3 Managing the Implementation of Organizational Change
- 4 Varieties of Expertise
- 5 Public (Community) Participation in Policymaking
- 6 Evidence and Values in Continuous Distribution Design
- 7 Organ Acceptance and Continuous Distribution
- 8 Constructed Collaboration
- Appendix
- References
- Index
Summary
The OPTN draws on a variety of expertise in designing organ allocation rules. Expertise arises from both explicit and tacit knowledge. Explicit knowledge includes generally accepted theories and empirical regularities that are accessible without first-hand experience of practice in some domain of knowledge. Tacit knowledge arises from experience, such as professional practice. In addition to this contributory tacit knowledge, it may also arise through interaction among participants in some domain of knowledge. Through its committee system, the OPTN taps the contributory knowledge of practitioners and patients and creates interactional tacit knowledge, especially among committee staff. Explicit knowledge arises from analysis of near universal longitudinal data on transplant candidates and other data collected within the transplantation system. These data support predictions of policy outcomes through simulation models and optimization tools utilizing machine learning.
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- Negotiating ValuesImplementing Change in the Allocation of Transplant Organs, pp. 76 - 99Publisher: Cambridge University PressPrint publication year: 2025
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