模糊规避的形成机制：基于可评价性假设的视角

模糊规避是指在相同奖赏的情况下,决策者会力图规避从主观上判断具有模糊概率的事件而偏好具有相同精确概率的事件。本研究使用同时评价、单独评价的研究范式从随机事件和自然事件两个领域来探讨模糊规避的形成机制。研究结果表明,当风险事件和模糊事件同时评价时,个体倾向于模糊规避;当风险事件和模糊事件单独评价时,模糊规避会消失。     

不同自尊者在赌博情境下的风险规避行为

为了考察不同自尊水平的个体在赌博情境下的风险规避行为,263名大学生被试同时完成外显Rosenberg量表、内隐联想测验和21点赌博游戏。实验结果发现,(1)随着风险的增加,所有被试都表现出风险规避;(2)在高外显自尊水平的个体中,低内隐自尊水平个体比高内隐自尊水平个体表现出更多的风险规避行为;在低内隐自尊的个体中,高外显自尊个体比低外显自尊个体表现出更多的风险规避行为。风险规避行为间接地反映出个体的防御倾向,结果提示,在风险情境中,高外显低内隐自尊个体表现出较高的自我防御倾向。     

Modelling the effects of semantic ambiguity in word recognition

Most words in English are ambiguous between different interpretations; words can mean different things in different contexts. We investigate the implications of different types of semantic ambiguity for connectionist models of word recognition. We present a model in which there is competition to activate distributed semantic representations. The model performs well on the task of retrieving the different meanings of ambiguous words, and is able to simulate data reported by Rodd, Gaskell, and Marslen-Wilson [J. Mem. Lang. 46 (2002) 245] on how semantic ambiguity affects lexical decision performance. In particular, the network shows a disadvantage for words with multiple unrelated meanings (e.g., bark) that coexists with a benefit for words with multiple related word senses (e.g., twist). The ambiguity disadvantage arises because of interference between the different meanings, while the sense benefit arises because of differences in the structure of the attractor basins formed during learning. Words with few senses develop deep, narrow attractor basins, while words with many senses develop shallow, broad basins. We conclude that the mental representations of word meanings can be modelled as stable states within a high-dimensional semantic space, and that variations in the meanings of words shape the landscape of this space.