We investigate the role of "prestige" and the effects of hierarchy in the sociology job market over six periods between 1986-2021. The sociology job market has undergone significant transformations over the past few decades, particularly with regard to the hiring of assistant professor positions. Many scholars have investigated the role of institutional prestige on hiring (Long, Allison, and McGinnis 1979, Headworth and Freese 2015, Gaddis 2015), examining the "ranking effect", the impact that a scholar's graduating department plays a role in their employment. We extend Burris (2004) by examining the meaning and role of prestige in the Ph.D. exchange network over time. Using stochastic block modeling (Snijders, van de Bunt, Steglich 2010), we partition these networks into three different groups, and which we characterize with respect to their average placement success. We demonstrate how these dynamic partitions correlate with ranking, even as the universities that constitute them change over time. Then, we use PageRank centrality, as a measure of social capital, to predict school ranking, and show the effects of block assignment on prestige. By controlling for different university characteristics (e.g., public vs. private), and using a dynamic, stochastic partitioning, we show how the meaning and impact of prestige in hiring has changed over the period of a tightening job market.

As teleworking arrangements remain prevalent beyond the pandemic, they continue to reshape daily routines, with potential implications for individuals’ social interactions. While teleworking reduces face-to-face interactions with colleagues, it eliminates commuting time and can offer greater flexibility, potentially increasing engagement with family and friends. Prior studies have shown that teleworking influences how individuals spend time with their social relationships and with whom they interact; however, limited research applies the structural information of personal networks to explore these dynamics.

This study addresses this gap using personal network data to examine how teleworking influences the frequency of interactions with different types of close contacts. It also considers the moderating roles of personality traits, namely extraversion, agreeableness and neuroticism. Utilising data from the Dutch Longitudinal Internet Studies for the Social Sciences (LISS) panel, we compare teleworkers and commuters, analysing their contact frequency with family and friends.

We hypothesise that teleworking is positively associated with interaction frequency with close contacts for both family and friend ties. We also anticipate personality traits to play a significant role in teleworkers’ social engagement. To test this, we conduct a moderation analysis using multi-level modelling to account for the nested structure of ego network data.

The findings will contribute to discussions on work-life balance and the social implications of telework, demonstrating how contextual factors shape personal networks. By identifying conditions under which teleworking advances or limits social contact for individuals of varying social dispositions, the study offers insights relevant for policies on remote work and social wellbeing.

The student decision-making process in the transition from high school to university or the labor market is affected by a complex interplay of personal aspirations, motivations or social relationships. Beyond educational performance and economic factors, the support received by students from family, peers, and other adults can shape students’ choices. The present contribution investigates how different types of social support —informational, emotional, and appraisal—are mobilized within students’ personal networks and which factors influence their choices. Personal network data were collected on a sample of high school students in Southern Italy using a multiple name generator to identify significant alters within three key social circles: family, school, and social environment. Information on alters’ characteristics, along with ego-alter and alter-alter ties, has been gathered through a name interpreter. Multilevel logistic regression models have been estimated, one for each kind of support, to examine the determinants of support provision while accounting for the hierarchical nature of the data. The models undertake alters (level 1) nested within egos (level 2), and incorporate both alter characteristics (type of relationship, gender, age), and ego attributes (gender, parental education, and specific soft skill scales, such as autonomy, problem-solving, leadership). Preliminary results highlight how the provision of social support varies based on the kind of relationship between alter and ego and individual characteristics.

Keywords: Egocentric network data, Multilevel logistic model, Peer effects, Social support

Note: We acknowledge financial support under the National Recovery and Resilience Plan (NRRP), Mission 4, Component 2, Investment 1.1, Call for tender No. 104 published on 2.2.2022 by the Italian Ministry of University and Research (MUR), funded by the European Union – NextGenerationEU– Project Title From high school to university: Assessing peers' influence in educational inequalities and performances – CUP F53D23006150006- Grant Assignment Decree No. 1060 adopted on 07/17/2023 by the Italian Ministry of Ministry of University and Research (MUR).

Nowadays, new teachers who enter the teaching profession do not stay long and leave

for other jobs in alarming numbers. In the UK, an estimated 40% of graduates who

enter the teaching profession leave in the first five years (Kyriacou and Kunc, 2007;

Sibieta, 2020), and for new teachers in shortage subjects such as math and physics,

the attrition rates are as high as 50% (Sibeta, 2020). To solve the problem of novice teacher attrition, researchers tried to explore the reasons why they leave to better understand the issue and then proposed some corresponding suggestions and theories in the process. Admittedly, it is a complicated issue, and such a leaving decision is usually caused by a combination of factors over a period of time. When studying the reasons of novice teachers’ attrition, previous

studies have focused on the personal characteristics of the novice teachers, such as

teachers’ resilience (Beltman, Mansfield and Price, 2011; Hong, 2012), while now a

few researchers have shifted their attention to the network aspects of these teachers

(Hokpins et al. 2019). Thus, I adopted social network theory, placing novice

teachers’ social networks in the center of my research, with both qualitative and quantitative data, I explored how their personal networks impact decision to stay or leave the teaching profession. To be specific, I studied 1) how novice teachers interact with other people in their networks, both with people internal and external to their work, including leaders, colleagues, students, parents of the students, and their own family members and friends, 2) how the opportunities, constraints and other things embedded in their personal networks influence their decision to leave the teaching career. The study is significant because it provides a better understanding of how novice teachers’ personal networks impact their leaving decision, and then hopefully the issue of novice teacher attrition can be decreased by coming up with methods to equip teachers with supportive networks that support their teaching career. Furthermore, when the attrition rates of novice teachers decrease, the attached challenges can also be relieved. To be more specific, the issue of teacher shortages, the high demand for teacher hiring can be relieved, and the

budgets used to recruit and train new teachers can be saved, and students

achievements do not need to be impacted by the leaving of their teachers.

We present a study examining how different teleworking modalities shape social interactions, focusing specifically on work-family conflict, interruptions during work activities, perceived managerial control, and various forms of social support. Our analysis draws on data from 4,000 employees across Switzerland, Spain, Germany, and the Netherlands, including detailed information on over 28,000 professional and household contacts.

Our findings illustrate multiple ways teleworking influences social relationships. For instance, the quality of the physical working environment emerges as a crucial factor in reducing interruptions over work activities and household conflicts. Interestingly, when teleworking leads to overtime and work intensification, it appears protective against conflicts with hierarchical superiors, who themselves represent an ambivalent source, simultaneously contributing to social conflict and providing essential social support. Furthermore, a mismatch between desired and actual telework intensity significantly predicts conflicts and negative experiences within social networks.

These results are based on the most extensive dataset to date of personal relationships within telework contexts, offering a significant contribution by integrating social network analysis into the literature on telework.