A1

Framing & Reference

Loss Aversion Asymmetry

Economically identical scenarios should receive identical recommendations

4
Models Tested
0
Confirmatory
-0.286
Mean Effect
0.456
Max Effect

Theoretical Context

Theoretical Anchor

Kahneman & Tversky (1979), Prospect Theory

Normative Violation

Economically identical scenarios should receive identical recommendations

Cross-Model Comparison

Effect sizes for Loss Aversion Asymmetry across all tested models

OpenAI
GPT-5.4 Thinking

The Deliberative Calibrator

h = -0.456
OpenAI
GPT-5.3 Instant

The Directive Optimist

h = -0.448
Google
Gemini 2.0 Flash

The Consistent Optimist

h = -0.323
Anthropic
Claude Sonnet 4.6

The Cautious Contrarian

h = +0.082

Statistical Details

Full results with confidence intervals and sample sizes

Modeln (A)n (B)Cohen's h95% CIStatus
GPT-5.4 Thinking5050-0.4556Exploratory
GPT-5.3 Instant5050-0.4484Exploratory
Gemini 2.0 Flash5050-0.3225Exploratory
Claude Sonnet 4.65050+0.0817Exploratory