scholarly journals Should Climate Scientists Fly?

2020 ◽  
Vol 40 (2) ◽  
pp. 157-203
Author(s):  
Jean Goodwin

 I inquire into argument at the system level, exploring the controversy over whether climate scientists should fly. I document participants’ knowledge of a skeptical argument that because scientists fly, they cannot testify credibly about the climate emergency. I show how this argument has been managed by pro-climate action arguers, and how some climate scientists have developed parallel reasoning, articulating a sophisticated case why they will be more effective in the controversy if they fly less. Finally, I review some strategies arguers deploy to use the arguments of others against them. I argue that only by attending to argument-making at the system level can we understand how arguers come to know the resources for argument available in a controversy and to think strategically about how to use them. I call for more work on argument at the system level

Author(s):  
Dhanush Dinesh ◽  
Dries Hegger ◽  
Joost Vervoort ◽  
Bruce M. Campbell ◽  
Peter P. J. Driessen

AbstractScience–policy engagement efforts to accelerate climate action in agricultural systems are key to enable the sector to contribute to climate and food security goals. However, lessons to improve science–policy engagement efforts in this context mostly come from successful efforts and are limited in terms of empirical scope. Moreover, lessons have not been generated systematically from failed science–policy engagement efforts. Such analysis using lessons from failure management can improve or even transform the efficacy of efforts. To address this knowledge gap, we examined challenges and failures faced in science–policy engagement efforts of the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS). We developed an explanatory framework inspired by Cash et al.’s criteria for successful knowledge systems for sustainable development: credibility, salience, and legitimacy, complemented with insights from the wider literature. Using this framework in a survey, we identified factors which explain failure. To effectively manage these factors, we propose a novel approach for researchers working at the science–policy interface to fail intelligently, which involves planning for failure, minimizing risks, effective design, making failures visible, and learning from failures. This approach needs to be complemented by actions at the knowledge system level to create an enabling environment for science–policy interfaces.


1998 ◽  
Author(s):  
Martin P. Charns ◽  
Victoria A. Parker ◽  
William H. Wubbenhorst
Keyword(s):  

2018 ◽  
Vol 4 (3) ◽  
pp. 228-244 ◽  
Author(s):  
Ivan J. Raymond ◽  
Matthew Iasiello ◽  
Aaron Jarden ◽  
David Michael Kelly
Keyword(s):  

2007 ◽  
Vol 51 (1-2) ◽  
pp. 43
Author(s):  
Balázs Polgár ◽  
Endre Selényi
Keyword(s):  

1997 ◽  
Vol 473 ◽  
Author(s):  
J. A. Davis ◽  
J. D. Meindl

ABSTRACTOpportunities for Gigascale Integration (GSI) are governed by a hierarchy of physical limits. The levels of this hierarchy have been codified as: 1) fundamental, 2) material, 3) device, 4) circuit and 5) system. Many key limits at all levels of the hierarchy can be displayed in the power, P, versus delay, td, plane and the reciprocal length squared, L-2, versus response time, τ, plane. Power, P, is the average power transfer during a binary switching transition and delay, td, is the time required for the transition. Length, L, is the distance traversed by an interconnect that joins two nodes on a chip and response time, τ, characterizes the corresponding interconnect circuit. At the system level of the hierarchy, quantitative definition of both the P versus td and the L-2 versus τ displays requires an estimate of the complete stochastic wiring distribution of a chip.Based on Rent's Rule, a well known empirical relationship between the number of signal input/output terminals on a block of logic and the number of gate circuits with the block, a rigorous derivation of a new complete stochastic wire length distribution for an on-chip random logic network is described. This distribution is compared to actual data for modern microprocessors and to previously described distributions. A methodology for estimating the complete wire length distribution for future GSI products is proposed. The new distribution is then used to enhance the critical path model that determines the maximum clock frequency of a chip; to derive a preliminary power dissipation model for a random logic network; and, to define an optimal architecture of a multilevel interconnect network that minimizes overall chip size. In essence, a new complete stochastic wiring distribution provides a generic basis for maximizing the value obtained from a multilevel interconnect technology.


Sign in / Sign up

Export Citation Format

Share Document