| 其他摘要 | Probability weighting refers to the assumption that the value of an outcome is multiplied by a decision weight that captures the subjective impact of that outcome on choice and that can deviate from the outcome's objective probability. Probability weighting is an important component of risky decision making and affects individuals' choice. Previous studies have found that in the field of risky decision making, the probability weighting function is nonlinear, and individuals tend to overweight small probabilities and underweight moderate and large probabilities. According to range frequency theory and decision by sampling, probability's subjective value is constructed from a series of binary, ordinal comparisons to a sample of probability values drawn from memory and its rank within the sample, and the sample reflects both the immediate distribution of probability values from the current decision's context and also the background, real-world distribution of probability values. Previous research analyzed the frequency with which English verbal probability occurred in natural language (i.e., the British National Corpus (BNC) World Edition), and found that the function has an inverse S-shape. Our previous study found that after translating English verbal probability into Chinese verbal probability, the corresponding numerical probabilities were not the same. Do Chinese and Western people exhibit the same probability weighting function? To address these issues, we conducted the following studies.
In Study 1，we analyzed the frequency with which Chinese verbal probability occurred in Weibo and Beijing Language and Culture University Corpus Center (BLCU Corpus Center, BCC), and compared the results with those of Western people. In Substudy 1 .1，we constructed a vocabulary of Chinese verbal probability, including 343 Chinese verbal probability. In Substudy 1.2, we recruited 162 participants to estimate the numerical probability equivalent of each verbal probability. In Substudies 1.3 and 1.4, we analyzed the frequency with which Chinese verbal probability occurred in Weibo and BCC, and reanalyzed the frequency with which English verbal probability occurred in BNC. The results showed that the compound invariance model fit the data best, either in Western or Chinese people. The curvature parameter y was larger in Chinese people than in Western people, indicating that the function in Chinese people was more linear than Western people. And the elevation parameter 8 was larger in Chinese people than in Western people, implying that Chinese people underweighted the probability of event occurrence. The results suggested that the tendency of overweighting small probabilities in Chinese people may be lower than that in Western people.
In Study 2, we conducted a meta-analysis to demonstrate whether there was a significant difference in the tendency of overweighting small probabilities between Chinese and Western people. This meta-analysis focusing on studies using the binary risky choice, in which participants were asked to choose between a safe option and a single-outcome risky option. The probabilities of risky options ranged from 00/o to 340/0. The tendency of overweighting small probabilities was measured by the proportion of risky option chosen in the gain domain, and the proportion of safe option chosen in the loss domain. After literature search and screening, a total of 137 datasets in 24 studies were included in the meta-analysis. The results showed that Western people showed a greater tendency of overweighting small probabilities than Chinese people.
The results of Studies 1 and 2 supported range-frequency theory and decision by sampling, which suggested people make binary, ordinal comparisons between probability and probability values were compared with a decision sample comprising a sample of values from memory. Decision by sampling also assumed that the distribution of probability in memory reflects the distribution of probability values in the world. Given that the memory retrieval of verbal probability is influenced by familiarity of verbal probability, in Study 3, we further explored whether familiarity of verbal probability affects individuals' probability weighting and risky decision making. In Substudies 3 .1 and 3.2, we investigated how familiarity of verbal probability affects individuals' risky decision making in the gain and loss domains, respectively. In Substudy 3.3, we explored whether there is a "verbal-numerical" framing effect and whether familiarity of verbal probability affects the "verbal-numerical" framing effect. In Substudy 3 .1 (N=110), we found that in the gain domain, familiarity of verbal probability was a significant predictor predicting an increased likelihood of selecting the risky option. In Substudy 3.2 (N=83), we found that in the loss domain, familiarity of verbal probability was a significant predictor predicting an decreased likelihood of selecting the risky option. In Substudy 3.3 (N=83), we compared participants' choices in verbal and numerical framing, and found a "verbal-numerical" framing effect, with participants choosing the risky option more often in the numerical framing than in the verbal framing. In addition, familiarity of verbal probability was a significant predictor predicting the "verbal-numerical" framing effect. Specifically, the more familiar participants were with the verbal probability, the more likely they were to choose the risky option in the verbal framing and to choose the safe option in the numerical framing.
In summary, we found that the tendency of overweighting small probabilities in Chinese samples was lower than that in Western samples, and familiarity of verbal probability was a significant predictor predicting an increased likelihood of selecting the risky option in the gain domain, while familiarity of verbal probability was a significant predictor predicting an decreased likelihood of selecting the risky option in the loss domain. We also found a "verbal-numerical" framing effect and that familiarity of verbal probability affects the "verbal-numerical" framing effect. The results provide new insights for future studies on verbal probability, future research could explore the mechanism of risky decision making under verbal probability, and conduct the nudging studies using the "verbal-numerical" framing effect. |
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