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1. chinaXiv:202004.00009 [pdf]

CAN Algorithm: An Individual Level Approach to identify Consequences and Norms Sensitivities and Overall Action/inaction Preferences in Moral Decision-making

Chuanjun Liu; Jiangqun Liao
Subjects: Psychology >> Psychological Measurement

Gawronski et al. (2017) developed a CNI model to measure an agent’s norms sensitivity, consequences sensitivity, and generalized inaction/action preferences when making moral decisions. However, the CNI model presupposed that an agent considers consequences—norms—generalized inaction/action preferences sequentially, which is untenable based on recent evidence. Moreover, the CNI model generates parameters at the group level based on binary categoric data. Hence, the C/N/I parameters cannot be used for correlation analyses or other conventional research designs. To solve these limitations, we developed the CAN algorithm to compute norms and consequences sensitivities and overall action/inaction preferences algebraically in a parallel manner. We re-analyzed the raw data of Gawronski et al.(2017) to test the methodological predictions. Our results demonstrate that: (1) the C parameter is approximately equal between the CNI model and CAN algorithm; (2) the N parameter under the CNI model approximately equals N/(1 – C) under the CAN algorithm; (3) the I parameter and A parameter are reversed around 0.5 – the larger the I parameter, the more the generalized inaction versus action preference and the larger the A parameter, the more overall action versus inaction preference; (4) tests of differences in parameters between groups with the CNI model and CAN algorithm led to almost the same statistical conclusion; (5) Parameters from the CAN algorithm can be used for correlational analyses and multiple comparisons, and this is an advantage over the parameters from the CNI model. The theoretical and methodological implications of our study were also discussed.

submitted time 2020-04-03 Hits6947Downloads718 Comment 0

2. chinaXiv:201810.00102 [pdf]

Where is the Embodiment Effect? The Hierarchical Access Priority Model

Chuanjun Liu; Jiangqun Liao; Kaiping Peng
Subjects: Psychology >> Cognitive Psychology

There are detailed theories and abundant empirical results regarding embodied cognition. However, embodiment effects are undergoing a replication crisis. Based on the hierarchical structure of embodiment tasks and the dual process property of embodiment phenomena, we propose the hierarchical access priority model (HAP). According to HAP, the generation of embodiment effects depends on the access priority of embodied variables to unconscious processes, and embodiment effects from different hierarchy levels show a contravariant relationship between effect size and stability. Theoretically, the stability of an embodiment effect is partly determined by the hierarchy of the embodied variable, and dissociation of the dual process moderates the effect size. Empirically, the hierarchical linear model analytic method should be considered for embodied research; the embodied variable could be designed as a mediating or moderating variable, and other possible masked mediating variables should be considered. HAP offers an insightful theoretical perspective for the embodiment replication crisis.

submitted time 2019-03-25 Hits9912Downloads1667 Comment 0

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