大学生对穷人的消极刻板印象及猜测偏向

College Students’Negative Stereotype and Guessing Bias Towards the Poor

主要考察大学生对穷人的消极刻板印象及猜测偏向。实验1中的两个单类内隐联想测验结果与前人研究基本一致:虽然被试对穷人热情的评价相对积极,但总体上认为穷人低能力、低热情。实验2通过源监测任务发现,在忘记特质词来源的情况下,被试倾向于猜测消极特质词来自贫困者,积极特质词来自小康者。研究不仅证实了大学生对穷人的消极刻板印象,而且进一步发现大学生存在对穷人的消极猜测偏向。

Culturally shared images portraying the poor are important resources for legalizing income inequality.According to Stereotype Content Model(SCM),competence and warmth are the two fundamental dimensions of stereotype.Low-status people are often seen as incompetent,and threatening individuals are often perceived as cold.The poor have lower income,less education,and worse jobs or no jobs,and they are often perceived as status threats by others.Some studies have shown that the poor are often considered with low competence and high warmth.At first glance,the high warmth evaluation,for the poor,has compensated the low competence evaluation.However,poor people’s warmth score is only at the middle or low level,and far lower than that of the middle-class.Based on the SCM and existing research results,hypothesis(H1)is made:The stereotype towards the poor is likely to be low-competence and low-warmth.The source-monitoring framework suggests that general knowledge or beliefs about sources can lead to biased guessing.Empirical studies also show that stereotypes are an important factor influencing guessing bias in source monitoring tasks:When the source memory is blurred,participants tend to guess that kitchenware is in the kitchen,and toiletries are in the bathroom;Medical advices come from doctors,and legal advices come from lawyers;“Worry about their attractiveness”comes from young people,and“worry about their health”comes from elderly people.Given people’s negative stereotype towards the poor and the effect of stereotype on guessing bias,it can be inferred:(H2)When the source is forgotten,participants tend to show negative guessing bias towards the poor.Two experiments were carried out to test the two hypotheses.College students participated in these experiments.Experiment 1 employed two single category-IATs(SC-IAT)to explore participants’implicit stereotypes towards the poor.SC-IAT is very useful,as it allows for testing the automatic association between“the poor”and“competence”(Exp1a)and the automatic association between“the poor”and“warmth”(Exp1b)without having a complementary target category(such as“the rich”).Experiment 2 required participants to complete the source monitoring task and estimated the guessing bias towards the poor via the two-high threshold source memory model(2HTSM).For the source monitoring task,participants were asked to perform a two-choice judgment for individually presented trait words(90 words)paired with their sources(the poor or well-off people)during the learning phase.During the testing phase,180 words were randomly presented on the computer screen.Participants were instructed to indicate whether the word had been presented.When a word was judged as an“old”word,participants then needed to indicate its source.In Experiment 1,when the words representing the poor and the words representing low-competence(Exp1a)and low-warmth(Exp1b)were categorized on one response key,participants responded faster;The D score in Exp1a was larger than that in Exp1b,suggesting that the poor were stereotyped as low-competence and low-warmth,and their competence was perceived as more negative.In Experiment 2,when trait-words were detected as“old”,whereas the source was forgotten,participants tended to guess that the negative trait words came from the poor,while the positive words came from well-off people,suggesting that participants had negative guessing bias towards the poor.Taken together,results from the two experiments provide evidences supporting our hypotheses:Participants not only hold negative stereotypes,but also show negative guessing bias towards the poor.These may further exacerbate income inequality.Being treated unfairly,the poor faces severe difficulties in the process of poverty alleviation.Therefore,future research needs to explore effective methods to decrease or eliminate the negative stereotypes and guessing bias towards the poor.