社会距离与分配差距对儿童有利不公平厌恶的影响

选取60名8-10岁儿童,采用迫选式独裁者游戏,考察个体与博弈对象的社会距离以及分配差距对儿童有利不公平厌恶的影响。结果发现：（1）在有利不公平条件下,与博弈对象社会距离越近,儿童对不公平分配提议的拒绝率越高;（2）分配差距越大,儿童对不公平分配提议的拒绝率越高;（3）社会距离和分配差距交互作用显著,在中等分配差距条件下,儿童对不公平分配提议拒绝率的社会距离效应最为明显。结果表明,社会距离和分配差距对儿童有利不公平厌恶有显著影响,在中度分配差距下社会距离具有更加明显的调节作用。     

A Monte Carlo evaluation of masked visual analysis in response‐guided versus fixed‐criteria multiple‐baseline designs

We developed masked visual analysis (MVA) as a structured complement to traditional visual analysis. The purpose of the present investigation was to compare the effects of computer‐simulated MVA of a four‐case multiple‐baseline (MB) design in which the phase lengths are determined by an ongoing visual analysis (i.e., response‐guided) versus those in which the phase lengths are established a priori (i.e., fixed criteria). We observed an acceptably low probability (less than .05) of false detection of treatment effects. The probability of correctly detecting a true effect frequently exceeded .80 and was higher when: (a) the masked visual analyst extended phases based on an ongoing visual analysis, (b) the effects were larger, (c) the effects were more immediate and abrupt, and (d) the effects of random and extraneous error factors were simpler. Our findings indicate that MVA is a valuable combined methodological and data‐analysis tool for single‐case intervention researchers.     

Within-culture variation in the content of stereotypes: Application and development of the stereotype content model in an Eastern European culture

There is little and unsystematic evidence about whether the content of stereotypes can vary within a culture. Using the Stereotype Content Model (SCM) as a theoretical framework, in two studies we examined the content of stereotypes in an Eastern European culture, namely Romania. Data were collected from four regions prototypical in terms of economic and social development in Romania, and we examined whether the content of stereotypes varies across these regions. As expected, the findings confirm the applicability of the SCM in Romania to reveal culture-specific stereotypes and provide initial support for within-culture variation in the content of stereotypes. We discuss, in particular, possible reasons for two main findings: a strong one-dimensional structure of stereotypes, and regional differences in stereotype content.     

Estimating Incremental Validity Under Missing Data

A common form of missing data is caused by selection on an observed variable (e.g., Z). If the selection variable was measured and is available, the data are regarded as missing at random (MAR). Selection biases correlation, reliability, and effect size estimates when these estimates are computed on listwise deleted (LD) data sets. On the other hand, maximum likelihood (ML) estimates are generally unbiased and outperform LD in most situations, at least when the data are MAR. The exception is when we estimate the partial correlation. In this situation, LD estimates are unbiased when the cause of missingness is partialled out. In other words, there is no advantage of ML estimates over LD estimates in this situation. We demonstrate that under a MAR condition, even ML estimates may become biased, depending on how partial correlations are computed. Finally, we conclude with recommendations about how future researchers might estimate partial correlations even when the cause of missingness is unknown and, perhaps, unknowable.     

Age slowing down in detection and visual discrimination under varying presentation times

The reaction time has been described as a measure of perception, decision making, and other cognitive processes. The aim of this work is to examine age‐related changes in executive functions in terms of demand load under varying presentation times. Two tasks were employed where a signal detection and a discrimination task were performed by young and older university students. Furthermore, a characterization of the response time distribution by an ex‐Gaussian fit was carried out. The results indicated that the older participants were slower than the younger ones in signal detection and discrimination. Moreover, the differences between both processes for the older participants were higher, and they also showed a higher distribution average except for the lower and higher presentation time. The results suggest a general slowdown in both tasks for age under different presentation times, except for the cases where presentation times were lower and higher. Moreover, if these parameters are understood to be a reflection of executive functions, these findings are consistent with the common view that age‐related cognitive deficits show a decline in this function.     

Sensitive Topics,Missing Data,and Refusal in Social Network Studies: An Ethical Examination

We describe our ethics‐driven process of addressing missing data within a social network study about accountability for racism, classism, sexism, heterosexism, cis‐sexism, ableism, and other forms of oppression among social justice union organizers. During data collection, some would‐be participants did not return emails and others explicitly refused to engage in the research. All refusals came from women of color. We faced an ethical dilemma: Should we continue to seek participation from those who had not yet responded, with the hopes of recruiting more women of color from within the network so their perspectives would not be tokenized? Or, should we stop asking those who had been contacted multiple times, which would compromise the social network data and analysis? We delineate ways in which current discussions of the ethics of social network studies fell short, given our framework and our community psychology (CP ) values. We outline literature that was helpful in thinking through this challenge; we looked outside of CP to the decolonization literature on refusal. Lessons learned include listening for the possible meanings of refusals and considering the level of engagement and the labor required of participants when designing research studies.     

Explaining White Opposition to Black Political Leadership: The Role of Fear of Racial Favoritism

Despite the election of America's first Black president, most non‐Hispanic Whites continue to oppose Black political leadership. The conventional explanation for White opposition is sheer racial prejudice, yet the available empirical evidence for this theory is inconsistent. I test an alternative theory that Whites perceive Black political leaders as a threat to their group's interests. Using a new survey measure and nationally representative panel data covering the 2008, 2010, and 2012 U.S. elections, I find that a majority of Whites perceive Black elected officials as likely to favor Blacks over Whites. Moreover, fear of racial favoritism predicts support for Barack Obama in both cross‐sectional models and fixed‐effects models of within‐person change, controlling for negative racial stereotypes. I replicate these findings using a separate cross‐sectional survey fielded after the 2014 election that controls for racial resentment. Collectively, these results suggest that perceptions of conflicting group interests—and not just prejudice—drive White opposition to Black political leadership.     

The Generalized Quantum Episodic Memory Model

Recent evidence suggests that experienced events are often mapped to too many episodic states, including those that are logically or experimentally incompatible with one another. For example, episodic over‐distribution patterns show that the probability of accepting an item under different mutually exclusive conditions violates the disjunction rule. A related example, called subadditivity, occurs when the probability of accepting an item under mutually exclusive and exhaustive instruction conditions sums to a number >1. Both the over‐distribution effect and subadditivity have been widely observed in item and source‐memory paradigms. These phenomena are difficult to explain using standard memory frameworks, such as signal‐detection theory. A dual‐trace model called the over‐distribution (OD) model (Brainerd & Reyna, 2008) can explain the episodic over‐distribution effect, but not subadditivity. Our goal is to develop a model that can explain both effects. In this paper, we propose the Generalized Quantum Episodic Memory (GQEM) model, which extends the Quantum Episodic Memory (QEM) model developed by Brainerd, Wang, and Reyna (2013). We test GQEM by comparing it to the OD model using data from a novel item‐memory experiment and a previously published source‐memory experiment (Kellen, Singmann, & Klauer, 2014) examining the over‐distribution effect. Using the best‐fit parameters from the over‐distribution experiments, we conclude by showing that the GQEM model can also account for subadditivity. Overall these results add to a growing body of evidence suggesting that quantum probability theory is a valuable tool in modeling recognition memory.