Social transformations and labour market entry:an investigation into university systems in emerging economies

Exclusion provokes a waste of talents and incalculable cultural and economic losses. Today, given the increasing number of qualified women and blacks, the lack of representation in top-job positions in knowledge-intensive occupations is hard to explain without considering network mechanisms in the entry process. Entering those occupations comprises training and supervision, collaboration, and mutual evaluation and often those tasks involve the same people. This implies that networks between agents, groups, and institutions form and are at the heart of learning, evaluation and promotion decisions. Thus, my thesis investigates network mechanisms of the entry process in academia with the empirical focus of South Africa and Mexico. First, I examine the tendency to form same-race and same-gender student-advisor relations in the educational phase. Then, I analyse this tendency closer asking whether it affects the doctoral productivity of the couples and whether its effect changes for students with high or low productivity profile. Lastly, I study how universities' prestige and first job-mobility affects scholars' future performance. My work highlights that the inertia of individual and institutional relations explains the lack of transformations in prestigious positions that, in turn, slow down transformations at lower levels. Besides this disheartening result, my work shows that when agents overcome the inertia, creating “uncommon” relations, they perform at the highest levels underlining the gains from inclusion

The role of early-career university prestige stratification on the future academic performance of scholars

Prestige and mobility are important aspects of academic life that play a critical role during early-career. After PhD graduation scholars have to compete for positions in the labour market. Unfortunately, many of them have few research products such that their inherent ability and skills remain mostly unobserved for hiring committees. Institutional prestige in this context is a key mechanism that signals the quality of candidates, and many studies have shown that a “good” affiliation can confer manyopportunities for future career development. We know little, however, about how changes of scholar’sinstitutional prestige during early-career relate to future academic performance. In this paper, we use an algorithm to rank universities based on hiring networks in Mexico. We distinguish three groups ofscholars that move Up,Down or Stay in the prestige hierarchy between PhD graduation and first job. After controlling for individual characteristics by matching scholars with equal training or the same first job institution, we find that scholars hired by their existing faculty sustain higher performance over their career in comparison to other groups. Interestingly, we find that scholars that move up the hierarchy exhibit, on average, lower academic performance than the other groups. We argue that the negative relation between upward ranking mobility and performance is related to the difficulties in changing research teams at an early-career stage and to the so-called “big-fish-small-pond” effect. We observe a high stratification of universities by prestige and a negative association between mobility and performance that can hinder the flows of knowledge throughout the science syste

Career Transitions and Trajectories: A Case Study in Computing

From artificial intelligence to network security to hardware design, it is well-known that computing research drives many important technological and societal advancements. However, less is known about the long-term career paths of the people behind these innovations. What do their careers reveal about the evolution of computing research? Which institutions were and are the most important in this field, and for what reasons? Can insights into computing career trajectories help predict employer retention? In this paper we analyze several decades of post-PhD computing careers using a large new dataset rich with professional information, and propose a versatile career network model, R^3, that captures temporal career dynamics. With R^3 we track important organizations in computing research history, analyze career movement between industry, academia, and government, and build a powerful predictive model for individual career transitions. Our study, the first of its kind, is a starting point for understanding computing research careers, and may inform employer recruitment and retention mechanisms at a time when the demand for specialized computational expertise far exceeds supply.Comment: To appear in KDD 201

How long do top scientists maintain their stardom? An analysis by region, gender and discipline: evidence from Italy

We investigate the question of how long top scientists retain their stardom. We observe the research performance of all Italian professors in the sciences over three consecutive four-year periods, between 2001 and 2012. The top scientists of the first period are identified on the basis of research productivity, and their performance is then tracked through time. The analyses demonstrate that more than a third of the nation's top scientists maintain this status over the three consecutive periods, with higher shares occurring in the life sciences and lower ones in engineering. Compared to males, females are less likely to maintain top status. There are also regional differences, among which top status is less likely to survive in southern Italy than in the north. Finally we investigate the longevity of unproductive professors, and then check whether the career progress of the top and unproductive scientists is aligned with their respective performances. The results appear to have implications for national policies on academic recruitment and advancement

Are female scientists less inclined to publish alone? The gender solo research gap

In solo research, scientists compete individually for prestige, sending clear signals about their research ability, avoiding problems in credit allocation, and reducing conflicts about authorship. We examine to what extent male and female scientists differ in their use of solo publishing across various dimensions. This research is the first to comprehensively study the “gender solo research gap” among all internationally visible scientists within a whole national higher education system. We examine the gap through mean “individual solo publishing rates” found in “individual publication portfolios” constructed for each Polish university professor. We use the practical significance/statistical significance difference (based on the effect-size r coefficient) and our analyses indicate that while some gender differences are statistically significant, they have no practical significance. Using a partial effects of fractional logistic regression approach, we estimate the probability of conducting solo research. In none of the models does gender explain the variability of the individual solo publishing rate. The strongest predictor of individual solo publishing rate is the average team size, publishing in STEM fields negatively affects the rate, publishing in male-dominated disciplines positively affects it, and the influence of international collaboration is negative. The gender solo research gap in Poland is much weaker than expected: within a more general trend toward team research and international research, gender differences in solo research are much weaker and less relevant than initially assumed. We use our unique biographical, administrative, publication, and citation database (“Polish Science Observatory”) with metadata on all Polish scientists present in Scopus (N = 25,463) and their 158,743 Scopus-indexed articles published in 2009–2018, including 18,900 solo articles