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It is generally accepted that neighboring nodes in financial networks are negatively assorted with respect to the correlation between their degrees. This feature would play an important 'damping' role in the market during downturns (periods of distress) since this connectivity pattern between firms lowers the chances of auto-amplifying (the propagation of) distress. In this paper we explore a trade-network of industrial firms where the nodes are suppliers or buyers, and the links are those invoices that the suppliers send out to their buyers and then go on to present to their bank for discounting. The network was collected by a large Italian bank in 2007, from their intermediation of the sales on credit made by their clients. The network also shows dissortative behavior as seen in other studies on financial networks. However, when looking at the credit rating of the firms, an important attribute internal to each node, we find that firms that trade with one another share overwhelming similarity. We know that much data is missing from our data set. However, we can quantify the amount of missing data using information exposure, a variable that connects social structure and behavior. This variable is a ratio of the sales invoices that a supplier presents to their bank over their total sales. Results reveal a non-trivial and robust relationship between the information exposure and credit rating of a firm, indicating the influence of the neighbors on a firm's rating. This methodology provides a new insight into how to reconstruct a network suffering from incomplete information.

It is generally accepted that neighboring nodes in financial networks are negatively assorted with respect to the correlation between their degrees. This feature would play an important 'damping' role in the market during downturns (periods of distress) since this connectivity pattern between firms lowers the chances of auto-amplifying (the propagation of) distress. In this paper we explore a trade-network of industrial firms where the nodes are suppliers or buyers, and the links are those invoices that the suppliers send out to their buyers and then go on to present to their bank for discounting. The network was collected by a large Italian bank in 2007, from their intermediation of the sales on credit made by their clients. The network also shows dissortative behavior as seen in other studies on financial networks. However, when looking at the credit rating of the firms, an important attribute internal to each node, we find that firms that trade with one another share overwhelming similarity. We know that much data is missing from our data set. However, we can quantify the amount of missing data using information exposure, a variable that connects social structure and behavior. This variable is a ratio of the sales invoices that a supplier presents to their bank over their total sales. Results reveal a non-trivial and robust relationship between the information exposure and credit rating of a firm, indicating the influence of the neighbors on a firm's rating. This methodology provides a new insight into how to reconstruct a network suffering from incomplete information.

It is generally accepted that neighboring nodes in financial networks are negatively assorted with respect to the correlation between their degrees. This feature would play an important 'damping' role in the market during downturns (periods of distress) since this connectivity pattern between firms lowers the chances of auto-amplifying (the propagation of) distress. In this paper we explore a trade-network of industrial firms where the nodes are suppliers or buyers, and the links are those invoices that the suppliers send out to their buyers and then go on to present to their bank for discounting. The network was collected by a large Italian bank in 2007, from their intermediation of the sales on credit made by their clients. The network also shows dissortative behavior as seen in other studies on financial networks. However, when looking at the credit rating of the firms, an important attribute internal to each node, we find that firms that trade with one another share overwhelming similarity. We know that much data is missing from our data set. However, we can quantify the amount of missing data using information exposure, a variable that connects social structure and behavior. This variable is a ratio of the sales invoices that a supplier presents to their bank over their total sales. Results reveal a non-trivial and robust relationship between the information exposure and credit rating of a firm, indicating the influence of the neighbors on a firm's rating. This methodology provides a new insight into how to reconstruct a network suffering from incomplete information.

It is generally accepted that neighboring nodes in financial networks are negatively assorted with respect to the correlation between their degrees. This feature would play an important 'damping' role in the market during downturns (periods of distress) since this connectivity pattern between firms lowers the chances of auto-amplifying (the propagation of) distress. In this paper we explore a trade-network of industrial firms where the nodes are suppliers or buyers, and the links are those invoices that the suppliers send out to their buyers and then go on to present to their bank for discounting. The network was collected by a large Italian bank in 2007, from their intermediation of the sales on credit made by their clients. The network also shows dissortative behavior as seen in other studies on financial networks. However, when looking at the credit rating of the firms, an important attribute internal to each node, we find that firms that trade with one another share overwhelming similarity. We know that much data is missing from our data set. However, we can quantify the amount of missing data using information exposure, a variable that connects social structure and behavior. This variable is a ratio of the sales invoices that a supplier presents to their bank over their total sales. Results reveal a non-trivial and robust relationship between the information exposure and credit rating of a firm, indicating the influence of the neighbors on a firm's rating. This methodology provides a new insight into how to reconstruct a network suffering from incomplete information.

It is generally accepted that neighboring nodes in financial networks are negatively assorted with respect to the correlation between their degrees. This feature would play an important 'damping' role in the market during downturns (periods of distress) since this connectivity pattern between firms lowers the chances of auto-amplifying (the propagation of) distress. In this paper we explore a trade-network of industrial firms where the nodes are suppliers or buyers, and the links are those invoices that the suppliers send out to their buyers and then go on to present to their bank for discounting. The network was collected by a large Italian bank in 2007, from their intermediation of the sales on credit made by their clients. The network also shows dissortative behavior as seen in other studies on financial networks. However, when looking at the credit rating of the firms, an important attribute internal to each node, we find that firms that trade with one another share overwhelming similarity. We know that much data is missing from our data set. However, we can quantify the amount of missing data using information exposure, a variable that connects social structure and behavior. This variable is a ratio of the sales invoices that a supplier presents to their bank over their total sales. Results reveal a non-trivial and robust relationship between the information exposure and credit rating of a firm, indicating the influence of the neighbors on a firm's rating. This methodology provides a new insight into how to reconstruct a network suffering from incomplete information.

It is generally accepted that neighboring nodes in financial networks are negatively assorted with respect to the correlation between their degrees. This feature would play an important 'damping' role in the market during downturns (periods of distress) since this connectivity pattern between firms lowers the chances of auto-amplifying (the propagation of) distress. In this paper we explore a trade-network of industrial firms where the nodes are suppliers or buyers, and the links are those invoices that the suppliers send out to their buyers and then go on to present to their bank for discounting. The network was collected by a large Italian bank in 2007, from their intermediation of the sales on credit made by their clients. The network also shows dissortative behavior as seen in other studies on financial networks. However, when looking at the credit rating of the firms, an important attribute internal to each node, we find that firms that trade with one another share overwhelming similarity. We know that much data is missing from our data set. However, we can quantify the amount of missing data using information exposure, a variable that connects social structure and behavior. This variable is a ratio of the sales invoices that a supplier presents to their bank over their total sales. Results reveal a non-trivial and robust relationship between the information exposure and credit rating of a firm, indicating the influence of the neighbors on a firm's rating. This methodology provides a new insight into how to reconstruct a network suffering from incomplete information.

It is generally accepted that neighboring nodes in financial networks are negatively assorted with respect to the correlation between their degrees. This feature would play an important 'damping' role in the market during downturns (periods of distress) since this connectivity pattern between firms lowers the chances of auto-amplifying (the propagation of) distress. In this paper we explore a trade-network of industrial firms where the nodes are suppliers or buyers, and the links are those invoices that the suppliers send out to their buyers and then go on to present to their bank for discounting. The network was collected by a large Italian bank in 2007, from their intermediation of the sales on credit made by their clients. The network also shows dissortative behavior as seen in other studies on financial networks. However, when looking at the credit rating of the firms, an important attribute internal to each node, we find that firms that trade with one another share overwhelming similarity. We know that much data is missing from our data set. However, we can quantify the amount of missing data using information exposure, a variable that connects social structure and behavior. This variable is a ratio of the sales invoices that a supplier presents to their bank over their total sales. Results reveal a non-trivial and robust relationship between the information exposure and credit rating of a firm, indicating the influence of the neighbors on a firm's rating. This methodology provides a new insight into how to reconstruct a network suffering from incomplete information.

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Lying exists in different human relationships as an inevitable behavior. The motives that people may have to lie range from prosocial ones to selfish ones. While people tend to stick to their moral default, the interaction of factors like social hierarchy and incentives leads to deviation causing the person to exhibit dishonest behavior. Many of these lies are selfish and subsequently harmful to others (Heyneman et al., 2008). However, people lie for their benefit and sometimes to help others. These different motivations and their in-built confluence and interactions in social hierarchies, where differences in perceived power and authority shape behavioral norms and expectations, come into play. while researchers highlight the impact of social rank on people’s dishonesty (Emerson, 1962), studies on the correlation between social rank and dishonest behavior show mixed results (Trautmann, 2012). Moreover, the incentives can also impact our dishonest behavior. Some researchers suggest that money or promotions can motivate lying and dishonesty (Deci, 1971; Belot & Ven De Ven, 2019). In contrast, some researchers didn’t find a correlation between incentives and dishonesty (Kaushik et al., 2022). Also, some research indicates an inverted U-shaped relationship where moderate rewards increase dishonesty up to a certain point, after which higher rewards decrease due to internal moral constraints (Mazar et al., 2008). Not just social hierarchy and incentive structures but also individuals’ moral defaults seem to impact the amount of lying. Recent research points to individual differences in lying based on their moral defaults (Gino et al., 2014; Speer et al., 2020). Based on this research people have individual differences in lying and are classified from the most honest to the most dishonest based on moral defaults. In the present study, we aim to reveal the combined effect of status level (high and low status) and different incentive structures (Baseline, Self-serving– Other-harming, Self-serving– Other-serving, Self-harming– Other-serving, Self-serving, Other-serving) on lying behavior and our second aim is to investigate whether people’s lying will be modulated by their moral default within the context of the study. Participants first will engage in a time estimation reaction time task, where they will play a game with their opponents with different ranks and we induce a middle rank to all of them. Afterward, they will engage in escalation to dishonesty task, where they will have the opportunity to lie in different incentive structures toward their high-rank or low-rank opponents (the same opponents of the social rank induction task). To assess moral default, we will analyze the variance in lying behavior across trials for each participant. This trial-by-trial assessment will identify individual differences in the extent of lying and dishonest behaviors, placing participants along a spectrum from most honest to most dishonest based on their behavioral tendencies. This index will help us understand the modulating effect of participants' moral defaults on their lying behavior under different incentive structures and social ranks.

preregistration Master thesis

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preregistration Master thesis

preregistration Master thesis

preregistration Master thesis

The fundamental differences in classroom social structure and the effect of teaching behavior on the unique patterns of classroom social structures were studied. Subjects included fifth-grade classrooms with female teachers in a small city school system. Eighteen classrooms with a total of 576 children fit these criteria. Instrumentation included sociometric variables rendered visible through the sociogram and teacher behavior variables measured by Flanders Interaction Analysis. The research confirmed that, in this sample, statistically significant relationships do exist between categories of verbal behaviors of teachers and patterns of peer relationships among their pupils. A broad spectrum relationship between direct and indirect teaching styles and peer relationship patterns was not confirmed. (A nine-item bibliography is included.) (MJM)

This paper deals with the issue of black-white differences in cognitive skills. Some authorities attribute these differences to differences in the environments of black and white homes. Others state that the differences are due to differences in genes, i.e., heredity. Scholars holding these two opposing views have become more or less entangled in an endless debate since Jensen published his article in 1969. The purpose of this paper is to suggest an alternative, structural explanation. The hypothesis proposed here is that black-white differences are due to adaptation to different cognitive requirements of their respective positions in the American caste system. In particular, it argues that the ascribed status of blacks which restricts them from participating in higher levels of American techno-economic organization has resulted in blacks evolving patterns of cognitive skills which are different from those developed by white Americans. This hypothesis has the advantage in that it can be applied to explain the observed differences between black males and black females as well as to minority-majority differences in other societies where similar pariah groups exist. Its significance for social policy lies in the fact that it identifies the cause rather than the symptoms of black educational problems. (Author/JM)

This paper deals with the issue of black-white differences in cognitive skills. Some authorities attribute these differences to differences in the environments of black and white homes. Others state that the differences are due to differences in genes, i.e., heredity. Scholars holding these two opposing views have become more or less entangled in an endless debate since Jensen published his article in 1969. The purpose of this paper is to suggest an alternative, structural explanation. The hypothesis proposed here is that black-white differences are due to adaptation to different cognitive requirements of their respective positions in the American caste system. In particular, it argues that the ascribed status of blacks which restricts them from participating in higher levels of American techno-economic organization has resulted in blacks evolving patterns of cognitive skills which are different from those developed by white Americans. This hypothesis has the advantage in that it can be applied to explain the observed differences between black males and black females as well as to minority-majority differences in other societies where similar pariah groups exist. Its significance for social policy lies in the fact that it identifies the cause rather than the symptoms of black educational problems. (Author/JM)

In this paper, the possibility of a bidirectional relationship between mass media use and political participation and a possible interaction of sex with other model variables are examined. A Two-Stage Least Squares analysis explores the mutual causation of mass media use and political participation, and separate analyses for male and female respondents explore the sex interactions. Data are from a 1971 survey of North Carolina. Mass media use is shown to have an effect on political participation in both the male and female subsamples. Political activity has a positive return effect on media use in the female subsample only. Results indicate that models which specify media use as a unidirectional cause of participation behavior are probably incorrect. Since empirical observations can lead to accurate inferences about the nature of a system only when the causal model is correctly specified, this analysis suggests wider use of techniques which allow the investigation of nonrecursive relationships. (Author/JM)

In this paper, the possibility of a bidirectional relationship between mass media use and political participation and a possible interaction of sex with other model variables are examined. A Two-Stage Least Squares analysis explores the mutual causation of mass media use and political participation, and separate analyses for male and female respondents explore the sex interactions. Data are from a 1971 survey of North Carolina. Mass media use is shown to have an effect on political participation in both the male and female subsamples. Political activity has a positive return effect on media use in the female subsample only. Results indicate that models which specify media use as a unidirectional cause of participation behavior are probably incorrect. Since empirical observations can lead to accurate inferences about the nature of a system only when the causal model is correctly specified, this analysis suggests wider use of techniques which allow the investigation of nonrecursive relationships. (Author/JM)

In this paper, the possibility of a bidirectional relationship between mass media use and political participation and a possible interaction of sex with other model variables are examined. A Two-Stage Least Squares analysis explores the mutual causation of mass media use and political participation, and separate analyses for male and female respondents explore the sex interactions. Data are from a 1971 survey of North Carolina. Mass media use is shown to have an effect on political participation in both the male and female subsamples. Political activity has a positive return effect on media use in the female subsample only. Results indicate that models which specify media use as a unidirectional cause of participation behavior are probably incorrect. Since empirical observations can lead to accurate inferences about the nature of a system only when the causal model is correctly specified, this analysis suggests wider use of techniques which allow the investigation of nonrecursive relationships. (Author/JM)

In this paper, the possibility of a bidirectional relationship between mass media use and political participation and a possible interaction of sex with other model variables are examined. A Two-Stage Least Squares analysis explores the mutual causation of mass media use and political participation, and separate analyses for male and female respondents explore the sex interactions. Data are from a 1971 survey of North Carolina. Mass media use is shown to have an effect on political participation in both the male and female subsamples. Political activity has a positive return effect on media use in the female subsample only. Results indicate that models which specify media use as a unidirectional cause of participation behavior are probably incorrect. Since empirical observations can lead to accurate inferences about the nature of a system only when the causal model is correctly specified, this analysis suggests wider use of techniques which allow the investigation of nonrecursive relationships. (Author/JM)