When and why framing effects are neither errors nor mistakes

Abstract Framing effects play a central role in the debate regarding human rationality. They violate the normative principle of description invariance , which states that merely redescribing options or outcomes in equivalent ways should not affect judgments or decisions. Description invariance is considered by many decision researchers to be “normatively unassailable”, and violations are widely regarded as demonstrations of systematic irrationality. This article develops an alternative perspective on invariance violations, applying Funder’s (1987) distinction between “errors” and “mistakes”. Description invariance implicitly assumes that (1) rational preferences must be complete and (2) frames do not convey choice-relevant information. We argue that both assumptions often do not hold. When they fail, framing effects in the laboratory are not “errors”, and they do not provide evidence for “mistakes” in natural environments. Furthermore, recent findings suggest that participants often do not regard different responses to different frames as unreasonable, and presenting them with arguments for and against description invariance has little effect on their views. Finally, we argue that similar lessons generalize to other coherence norms, such as procedure invariance and independence of irrelevant alternatives.

Authors

Institutions

Publication Details

Journal
Mind & Society
Published
2025-10-17
DOI
https://doi.org/10.1007/s11299-025-00338-9
Citations
1
Primary Topic
Decision-Making and Behavioral Economics
Type
article
Field-Weighted Citation Impact
2.27

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

When and why framing effects are neither errors nor mistakes

Shlomi Sher, Xingyu Shirley Liu, Craig R. M. McKenzie, Leo J. Kleiman-Lynch
1 citations
Mind & Society
Decision-Making and Behavioral Economics
2.27
article

When and why framing effects are neither errors nor mistakes

Shlomi Sher, Xingyu Shirley Liu, Craig R. M. McKenzie, Leo J. Kleiman-Lynch
article en
1 citations

Abstract

Abstract Framing effects play a central role in the debate regarding human rationality. They violate the normative principle of description invariance , which states that merely redescribing options or outcomes in equivalent ways should not affect judgments or decisions. Description invariance is considered by many decision researchers to be “normatively unassailable”, and violations are widely regarded as demonstrations of systematic irrationality. This article develops an alternative perspective on invariance violations, applying Funder’s (1987) distinction between “errors” and “mistakes”. Description invariance implicitly assumes that (1) rational preferences must be complete and (2) frames do not convey choice-relevant information. We argue that both assumptions often do not hold. When they fail, framing effects in the laboratory are not “errors”, and they do not provide evidence for “mistakes” in natural environments. Furthermore, recent findings suggest that participants often do not regard different responses to different frames as unreasonable, and presenting them with arguments for and against description invariance has little effect on their views. Finally, we argue that similar lessons generalize to other coherence norms, such as procedure invariance and independence of irrelevant alternatives.

Mind & SocietyVol. 24(2)
University of San Diego (US), Pomona College (US), UC San Diego Health System (US)
National Science Foundation, James S. McDonnell Foundation
Openalex Percentile: Top 11%
Decision-Making and Behavioral Economics
2.27
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.