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Improving carbon footprint estimates of food items with a simple seeding procedure

Improving carbon footprint estimates of food items with a simple seeding procedure Laypeople's estimates of carbon footprints have repeatedly shown to be deficient, which may hinder targeted behavior change to reduce CO2 emissions. In an online study (N = 127), a vast underestimation of carbon footprints for 60 food items was observed in an on average highly educated convenience sample, confirming a lack of carbon footprints knowledge. Then, target carbon footprint values for a small subset of 15 “seeding” items were provided, which led to a large improvement in a second estimate for both the seeding as well as the remaining transfer items. A lens model analysis showed that participants adjusted the weighting of several predictors in the correct direction due to this simple intervention. It is argued that although almost 30 years old, “seeding the knowledge base” has probably been neglected as an effective low‐cost intervention for improving quantitative knowledge of the public. This is especially important concerning societal problems that rely on adequate numerical knowledge for behavior regulation. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Applied Cognitive Psychology Wiley

Improving carbon footprint estimates of food items with a simple seeding procedure

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Publisher
Wiley
Copyright
© 2023 John Wiley & Sons, Ltd.
ISSN
0888-4080
eISSN
1099-0720
DOI
10.1002/acp.4060
Publisher site
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Abstract

Laypeople's estimates of carbon footprints have repeatedly shown to be deficient, which may hinder targeted behavior change to reduce CO2 emissions. In an online study (N = 127), a vast underestimation of carbon footprints for 60 food items was observed in an on average highly educated convenience sample, confirming a lack of carbon footprints knowledge. Then, target carbon footprint values for a small subset of 15 “seeding” items were provided, which led to a large improvement in a second estimate for both the seeding as well as the remaining transfer items. A lens model analysis showed that participants adjusted the weighting of several predictors in the correct direction due to this simple intervention. It is argued that although almost 30 years old, “seeding the knowledge base” has probably been neglected as an effective low‐cost intervention for improving quantitative knowledge of the public. This is especially important concerning societal problems that rely on adequate numerical knowledge for behavior regulation.

Journal

Applied Cognitive Psychology – Wiley

Published: May 1, 2023

Keywords: carbon footprints; environmental knowledge; numerical estimation; seeding

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