Likelihood of Split

Examples of Likelihood of Split in the following topics:

• Marital Residence

  • A scientific survey of over 1,000 married men and women in the United States found that those who moved in with a lover before engagement or marriage reported significantly lower quality marriages and a greater possibility for splitting up than other couples.
  • But over the years, evidence indicating cohabiting increases the likelihood of split has always been more prevalent than evidence that suggests it is helpful.
  • A scientific survey of over 1,000 married men and women in the United States found that those who moved in with a lover before engagement or marriage reported significantly lower quality marriages and a greater possibility for splitting up than other couples.
  • In California, such couples are defined as people who "have chosen to share one another's lives in an intimate and committed relationship of mutual caring," including having a "common residence, and are the same sex or persons of opposite sex if one or both of the persons are over the age of 62. "
  • This figure shows that roughly 5% of households in the United States are made up of cohabiting couples of various types: heterosexual, gay, or, lesbian.

• CONCOR

  • In a sense, the approach is asking "how similar is the vector of similarities of actor X to the vector of similarities of actor Y?"
  • We used Network>Roles & Positions>Structural>CONCOR, and set the depth of splits = 2 (that is, divide the data twice).
  • The second panel shows the two splits.
  • On the second split these were sub-divided into {1, 4}, {5, 2,7}, {8, 3, 9}, and {6, 10}.
  • For the CONCOR two-split (four group) model, this r-squared is .451.

• Age and Race

  • Aging does not result in similar outcomes for members of different races.
  • There is evidence that black senior citizens are more likely to be abused - both physically and psychologically and suffer greater financial exploitation than do white senior citizens.Further, recent demographic profiles suggest that social aging varies across racial groups, and demonstrates that minority elders (especially Hispanic and African American identified) typically enter later life with less education, less financial resources, and less access to health care than their white counterparts.Finally, researchers have noted that minority groups' greater likelihood of facing patterns of structural disadvantage throughout the life course, such as racial discrimination, poverty, and fewer social, political, and economic resources on average, create significant racial variations in the stages or age-related trajectories of racial minorities and majorities that may be observed at all points of the life span, and contribute to disparities in health, income, self-perceived age, mortality, and morbidity.
  • As a result, sociologists often explore the timing (in both subjective and objective conceptualizations of age) of varied life events within and between racial groups while exploring ways that age-related disparities influence the structural realities and bio-social outcomes of people located within different racial groups.

• The Dynamics of Poverty

  • Poverty operates in a dynamic cycle, with the effects of poverty increasing the likelihood that it will be transferred between generations.
  • This perpetuation of deprivation is the cycle of poverty.
  • In this way, inadequate or lack of education can perpetuate poverty.
  • Finally, poverty increases the risk of homelessness.
  • Slum-dwellers, who make up a third of the world's urban population, live in poverty no better, if not worse, than rural people, who are the traditional victims of poverty in the developing world.

• Elements of Socialization

  • 3) the cultivation of sources of meaning, or what is important, valued, and to be lived for
  • There is also a greater likelihood of more formal relationships due to situational contexts (e.g., work environment), which moderates down the affective component.
  • 4) there is a sharp split between supervisors and lower participants
  • When the goal of an institution is resocialization of deviants, coercion is frequently involved.
  • There are, unfortunately, a number of examples of such children that have been well-documented, including:

• Migration

  • The likelihood of a given individual in the U.S. moving to another place in the U.S. in any given year has declined over the last 40 years.Only about 1 in 10 Americans have moved in the last year, which is about half the proportion that changed residences annually in the 1960s.The reduction in moves is attributable to aging populations (older people are less likely to move) and an increase in dual-career couples.Those who do move are generally driven by jobs.
  • Close to 37% of Americans have never moved from the community in which they were born.There are wide variations in native inhabitants, however: 76% of Texans were born in-state while only 14% of Nevadans were born in-state.Some states lose a large number of people who were born in the state as well, like Alaska, where only 28% of the people born in that state have remained there.Immigration is often a controversial topic, for a variety of reasons, though many have to do with competition between those already living in the destination location and those arriving in that location.One recent study finds that one type of competition between immigrants and non-immigrants may be overstated.Some people have suggested that natives' opportunities to attend college are negatively impacted through competition with immigrants.Neymotin (2009) finds that competition with immigrants does not harm the educational outcomes of U.S. natives and may in fact facilitate college attending.

• High School Dropouts

  • Dropouts have a greater likelihood of being arrested.
  • Not all students have an equal risk of dropping out.
  • The relationships students have with their peers also influence a student's likelihood of dropping out.
  • As mentioned above, grade retention increases the likelihood that a student will drop out of school.
  • Recall some of the reasons why students in the U.S. may drop out of high school and the potential consequences of dropping out

• Introduction to comparing two relations for the same set of actors

  • The basic question of bivariate analysis of network data is whether the pattern of ties for one relation among a set of actors aligns with the pattern of ties for another relation among the same actors.
  • Three of the most common tools for bivariate analysis of attributes can also be applied to the bivariate analysis of relations:
  • Does the central tendency of one relation differ significantly from the central tendency of another?
  • If we know that a relation of one type exists between two actors, how much does this increase (or decrease) the likelihood that a relation of another type exists between them?
  • For example, what is the effect of a one dollar increase in the volume of trade between two nations on the volume of tourism flowing between the two nations?

• The probability of a dyadic tie: Leinhardt's P1

  • Network>P1 is a regression-like approach that seeks to predict the probability of each of these kinds of relationships for each pair of actors.
  • It is also a function of the overall density of the network (theta).
  • The technical aspects of the estimation of the P1 model are complicated, and maximum likelihood methods are used.A G-square (likelihood ratio chi-square) badness of fit statistic is provided, but has no direct interpretation or significance test.
  • Theta = -1.6882 refers to the effect of the global density of the network on the probability of reciprocated or asymmetric ties between pairs of actors.
  • Rho = 3.5151 refers to the effect of the overall amount of reciprocity in the global network on the probability of a reciprocated tie between any pair of actors.

• Introduction to explaining the relations among actors in a network

  • Models like these are very useful for examining the relationships among relational and non-relational attributes of individuals.
  • One of the most distinctive ways in which statistical analysis has been applied to social network data is to focus on predicting the relations of actors, rather than their attributes.
  • Models like this are focusing directly on a very sociological question: what factors affect the likelihood that two individuals will have a relationship?
  • This "homophily" hypothesis is at the core of many theories of differentiation, solidarity, and conflict.
  • This type of model -- a probability model for the presence/absence of each possible relation in a graph as a function of network structures -- is one of the major continuing areas of development in social network methods.