切忌班门弄斧?低估在评价者擅长领域展现能力的好处

doi:10.3724/SP.J.1041.2023.00766

摘要/Abstract

摘要：

人需要展现自己以脱颖而出, 常常预测在他人擅长领域展现能力会暴露缺点导致差评, 因而忌讳班门弄斧。然而这种预测准确吗?8项研究(N = 1, 888)要求候选人选择在评价者擅长或不擅长领域展示能力, 要求评价者从班门弄斧和不班门弄斧者中择一录取, 发现候选人低估班门弄斧所得评价。导致此预测偏差的原因是, 评价者依据提及其擅长领域时的自豪感决策, 故给班门弄斧者好评, 候选人依据能力是否容易被看清来选择领域, 担心班门弄斧暴露缺点。

关键词: 预测偏差, 自我中心, 能力, 自豪, 判断与决策

Abstract:

Job candidates and competitors aim to earn admission or high ratings. People tend to avoid displaying their skills in front of an expert due to the prediction that they will be rated unfavorably because the expert can accurately evaluate their level of skill. However, is this prediction accurate? The present research proposes a misprediction: candidates will undervalue the advantages of showing skills in front of an expert. This is because evaluators partially base their evaluations on the pride elicited by alluding to their expertise, whereas candidates base their predictions on whether their competence will be accurately evaluated but neglect evaluators’ pride.

Eight studies (N = 1, 888) demonstrated the proposed misprediction and tested its underlying mechanism. In Study 1, we assigned the participants to the candidate or the evaluator condition. The candidates made an incentive-compatible prediction on how they would be more likely to be admitted by displaying their skills in front of an expert or a non-expert. The evaluators admitted one between a candidate displaying skills in the evaluators’ area of expertise and a candidate displaying skills outside the evaluators’ area of expertise. The results showed that the evaluators preferred the candidate who showcased skills in the evaluators’ area of expertise. However, the candidates avoided doing so, which reduced their chances of admission.

Studies 2 and 3 replicated the results in Study 1 with different competition forms (promotion or elimination) and in the case where candidates were assigned to display skills in or outside the evaluators’ area of expertise. These studies ruled out two alternative explanations that the evaluators preferred the candidate who showcased skills in the evaluators’ area of expertise solely because they were similar to the candidate or could easily evaluate the candidate.

Studies 4 and 5 manipulated the candidates’ motivation to win the competition and their level of competence, respectively, to test whether they avoided displaying skills in front of experts due to the concern that their competence could be evaluated accurately by experts. The results indicated that the candidates showed a stronger misprediction and were less likely to showcase skills in front of experts when they highly (vs. less) desired to win the competition or had a lower (vs. moderate and higher) competence.

Study 6 prompted the candidates to empathize with evaluators. We asked the candidates to think about their feelings when others made references to their expertise. As a result, the candidates were aware of their pride and made a more accurate prediction.

Study 7 manipulated the evaluators’ pride to test whether they preferred the candidate who displayed skills in the evaluators’ area of expertise because that they felt pride when their expertise was referred to. The results revealed that the evaluators with lower (vs. higher) pride were less likely to admit the candidates who displayed skills in the evaluators’ area of expertise.

In Study 8, we recorded the participants’ real-time thoughts during their decision making. The results again showed that the candidates focused on their competence during their decision-making process, whereas the evaluators’ preferences were affected by their pride. In addition, the real-time thoughts led to the underestimation about the benefits of displaying skills in front of an expert.

We reveal that people fail to accurately predict the effect of a self-presentation strategy. Candidates undervalue the strategy of displaying skills in front of experts due to the empathy gap that they neglect the pride experienced by experts. Consequently, candidates mistakenly avoid displaying skills in front of experts and thus miss the chance to earn admission. Besides, we offer a feasible approach to reduce such a bias. Our findings encourage candidates to empathize with evaluators and strategically perform to experts.

Key words: misprediction, egocentrism, competence, pride, judgment and decision making

中图分类号:

B849: C91

邱天, 江南, 陆静怡. (2023). 切忌班门弄斧?低估在评价者擅长领域展现能力的好处. 心理学报, 55(5), 766-780.

QIU Tian, JIANG Nan, LU Jingyi. (2023). Undervaluing the advantages of displaying skills in front of an expert. Acta Psychologica Sinica, 55(5), 766-780.

图/表 9

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编码类别	候选人	评价者
能力是否容易(被)看清	评委在不擅长领域看不出瑕疵。	在擅长领域更容易发现缺陷。
有自豪感	-	对自己擅长的领域更有好感。
彼此相似	与评委口味相似更易得高分。	与选手有共同爱好。
能力是否容易评价	-	擅长领域很容易评价。
未按要求解释理由¹（¹该分类指被试没有按照要求解释选择某领域或某候选人的原因。例如, 类似“擅长领域更加分”的作答仅反映因变量本身, 即“我偏好擅长领域”, 而未解释“我为什么偏好擅长领域”。）	选评委不擅长领域更可能晋级。	擅长领域更加分。
其他	自己喜欢。	淘汰小李会被质疑不配当评委。

编码类别	候选人	评价者
能力是否容易(被)看清	评委在不擅长领域看不出瑕疵。	在擅长领域更容易发现缺陷。
有自豪感	-	对自己擅长的领域更有好感。
彼此相似	与评委口味相似更易得高分。	与选手有共同爱好。
能力是否容易评价	-	擅长领域很容易评价。
未按要求解释理由¹（¹该分类指被试没有按照要求解释选择某领域或某候选人的原因。例如, 类似“擅长领域更加分”的作答仅反映因变量本身, 即“我偏好擅长领域”, 而未解释“我为什么偏好擅长领域”。）	选评委不擅长领域更可能晋级。	擅长领域更加分。
其他	自己喜欢。	淘汰小李会被质疑不配当评委。

选择理由	候选人−选擅长 (n = 12)	候选人−选不擅长 (n = 56)	候选人 (n = 68)	评价者−选擅长 (n = 55)	评价者−选不擅长 (n = 17)	评价者 (n = 72)
能力是否容易(被)看清	5 (41.67%)	42 (75.00%)	47 (69.12%)	9 (16.36%)	13 (76.47%)	22 (30.56%)
有自豪感	0 (0.00%)	0 (0.00%)	0 (0.00%)	17 (30.91%)	0 (0.00%)	17 (23.61%)
彼此相似	3 (25.00%)	0 (0.00%)	3 (4.41%)	5 (9.09%)	0 (0.00%)	5 (6.94%)
能力是否容易评价	0 (0.00%)	0 (0.00%)	0 (0.00%)	3 (5.45%)	0 (0.00%)	3 (4.17%)
未按要求解释理由	2 (16.67%)	14 (25.00%)	16 (23.53%)	17 (30.91%)	2 (11.76%)	19 (26.39%)
其他	2 (16.67%)	0 (0.00%)	2 (2.94%)	4 (7.27%)	2 (11.76%)	6 (8.33%)

选择理由	候选人−选擅长 (n = 12)	候选人−选不擅长 (n = 56)	候选人 (n = 68)	评价者−选擅长 (n = 55)	评价者−选不擅长 (n = 17)	评价者 (n = 72)
能力是否容易(被)看清	5 (41.67%)	42 (75.00%)	47 (69.12%)	9 (16.36%)	13 (76.47%)	22 (30.56%)
有自豪感	0 (0.00%)	0 (0.00%)	0 (0.00%)	17 (30.91%)	0 (0.00%)	17 (23.61%)
彼此相似	3 (25.00%)	0 (0.00%)	3 (4.41%)	5 (9.09%)	0 (0.00%)	5 (6.94%)
能力是否容易评价	0 (0.00%)	0 (0.00%)	0 (0.00%)	3 (5.45%)	0 (0.00%)	3 (4.17%)
未按要求解释理由	2 (16.67%)	14 (25.00%)	16 (23.53%)	17 (30.91%)	2 (11.76%)	19 (26.39%)
其他	2 (16.67%)	0 (0.00%)	2 (2.94%)	4 (7.27%)	2 (11.76%)	6 (8.33%)