Sampling Richness and Qualitative Integrity: Challenges for Research With Families

Sampling is one of the most difficult and contentious aspects of qualitative research design. There are few guidelines for sampling decisions or for understanding saturation in qualitative family research. The authors frame the problematic of data quality in the selection of units of analysis and observation and consider how to enhance sample richness. They outline considerations for data quantity and sample size as well as case‐ and variable‐based approaches. With multiple examples from recent and classic studies to illustrate the consequences of sampling decisions, they explore links between saturation and validity. Finally, they encourage researchers to craft a coherent statement on qualitative integrity to demonstrate how their sampling decisions are rooted in epistemology, theory, and richness and quality of data.     

Associations Between Friendship,Sympathy, and Prosocial Behavior Toward Friends

The current study examined the associations between multiple aspects of the friend relationship (connection, companionship, psychological control) and global prosocial behavior toward friends. Participants included 467 early adolescents (M age of child = 13.32, SD = 1.05, 49% female, 69% European American), and data were collected at two time points, roughly 1 year apart. Structural equation modeling suggested that friend psychological control was negatively associated with prosocial behavior toward friends, while friend connection was positively associated (via adolescent sympathy). Discussion focuses on the friend relationship as an important influence on adolescent sympathy and prosocial behavior toward friends.     

Yearlong physical activity and health-related quality of life in older Japanese adults: the Nakanojo Study

We hypothesized that the health-related quality of life (HRQOL) would be poorer in physically inactive older adults. This was tested in a sample of 73 male and 108 female free-living healthy Japanese participants, age 65-85 years. We measured accelerometer step counts and their metabolic equivalents (METs) throughout each 24-hr period for 1 year. At the end of the year, HRQOL was assessed. Physical activity was grouped into quartiles. HRQOL was poorer in the lowest quartiles of participants with respect to both step count and duration of activity >3 METs; however, our sample showed no better HRQOL in those participants exceeding minimum standards of daily physical activity, corresponding to counts of around 5,500 and 4,500 steps/day and durations of around 13 and 14 min/day in men and women, respectively. Causation cannot be demonstrated from this cross-sectional study, but nevertheless we suggest that elderly individuals should be encouraged to meet such standards of habitual physical activity.     

Implementing the right project structure to achieve coopetitive innovation projects

This research focuses on the project structure used by coopetitors to achieve common innovation projects. Scholars have recently identified an original but complex project structure that they call the Coopetitive Project Team (CPT). However, other project structures can also be implemented by coopetitors to achieve innovation. Therefore, we address the following question: for which types of innovation projects is CPT appropriate? We argue that coopetitors need to use CPT for high-risk and high-cost projects when the aim is to develop radical innovation. CPT allows coopetitors not only to develop innovation capabilities through close resource and knowledge sharing but also to manage the risk of opportunism. Conversely, coopetitors should use another project structure, Separated Project Teams (SPTs), for low-cost and low-risk projects when the aim is to develop incremental innovation. The SPT design allows coopetitors both to achieve the goal of the project and to minimize the risk of opportunism. To confirm our assumptions, we studied the project portfolios of Airbus and Thales, two firms in the space satellite industry. Our findings confirm that coopetitors should implement CPTs to handle innovation projects that are costly, risky and highly innovative. CPTs permit the sharing of knowledge and the management of high opportunism risk, both of which are necessary to achieve radical innovation. Conversely, coopetitors rely on SPTs for low-cost projects that require a low degree of knowledge sharing, thus avoiding the risk of opportunism in achieving their incremental innovation objectives.     

Teacher–child relationships in the context of poverty: the role of frequent school mobility

Children's relationships with their teachers are critical for classroom-based learning, but children growing up in poverty may be at risk for lower-quality relationships with teachers. Little is known about how changing schools, one poverty-related risk, affects teacher–child relationships. Using growth curve models that control for a host of other poverty-related risks, this study explores the association between children changing schools frequently (defined as three or more school moves) between preschool and third grade and the quality of their relationships with their teachers over these five years in a low-income, ethnic-minority sample. Children who frequently moved schools were reported to be less close to their teachers in third grade and experienced steeper declines in closeness than children who did not change schools frequently. Moreover, the effects of frequent school mobility at third grade were robust to other poverty-related risks, including residential mobility, parental education risk, family income, and single-parent households. Changing schools was unrelated to children's conflict with teachers. We discuss these findings in the context of policies that support students’ transitions when changing schools.     

From Policy to Practice: Exploring Practitioners’ Perspectives on Social Enterprise Policy Claims

While there has been significant academic focus on social enterprise policy for a number of years now, the links between policy and the practice of social enterprise have received comparatively less attention. Scotland is recognised as having a particularly supportive environment for social enterprise; the Scottish Government has publicly endorsed social enterprise and made considerable investment into the sector. Based upon an in-depth qualitative analysis of the perceptions of social enterprise practitioners and stakeholders across Scotland, we explore whether the rhetoric of support matches practitioners experience of ‘doing’ social enterprise. Reviewing emerging issues and reflecting upon the complex nature of the Scottish context, including in relation to welfare reform, we find that in contrast to the claims of politicians, the attitude of local authorities in Scotland, coupled with a lack of understanding of the needs and requirements of social enterprise at the local authority level, has led to a rather more ‘patchwork’ picture than the rhetoric would seem to suggest. While some local authorities recognise the potential of social enterprise for their local economies and privilege and encourage cooperation, others are less inclined to openly support social enterprise, particularly those that are small in scale. Underpinning these contentions, we argue, are unrealistic expectations about the prospects of social enterprises being able to become ‘sustainable’, and how this could be achieved.     

Inference based on progressive Type I interval censored data from log-normal distribution

This article considers inference for the log-normal distribution based on progressive Type I interval censored data by both frequentist and Bayesian methods. First, the maximum likelihood estimates (MLEs) of the unknown model parameters are computed by expectation-maximization (EM) algorithm. The asymptotic standard errors (ASEs) of the MLEs are obtained by applying the missing information principle. Next, the Bayes’ estimates of the model parameters are obtained by Gibbs sampling method under both symmetric and asymmetric loss functions. The Gibbs sampling scheme is facilitated by adopting a similar data augmentation scheme as in EM algorithm. The performance of the MLEs and various Bayesian point estimates is judged via a simulation study. A real dataset is analyzed for the purpose of illustration.