In this large-scale research based on bibliometric, biographical and administrative data, we examine how gender disparities in international research collaboration differ by collaboration intensity, academic position, age, and academic discipline. The following are the major findings: (1) While female scientists exhibit a higher rate of general, national, and institutional collaboration, male scientists exhibit a higher rate of international collaboration. (2) An aggregated picture of gender disparities hides a more nuanced cross-disciplinary picture of them. (3) An analysis of international research collaboration at three separate intensity levels (low, medium, and high) reveals that male scientists dominate in international collaboration at each level. However, at each level, there are specific disciplines in which females collaborate internationally more than males. Furthermore (4), gender disparities in international research collaboration are clearly linked with age: they are the lowest and statistically insignificant for young scientists and the highest and statistically significant for the oldest scientists. Finally, we estimate the odds ratios of being involved in international research collaboration using an analytical linear logistic model. The examined sample includes 25,463 internationally visible Polish university professors from 85 universities, grouped into 24 disciplines, and 158,743 Scopus-indexed articles.
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.
Biological age is an important sociodemographic factor in studies on academic careers (research productivity, scholarly impact, and collaboration patterns). It is assumed that the academic age, or the time elapsed from the first publication, is a good proxy for biological age. In this study, we analyze the limitations of the proxy in academic career studies, using as an example the entire population of Polish academic scientists and scholars visible in the last decade in global science and holding at least a PhD (N = 20,569). The proxy works well for science, technology, engineering, mathematics, and medicine (STEMM) disciplines; however, for non-STEMM disciplines (particularly for humanities and social sciences), it has a dramatically worse performance. This negative conclusion is particularly important for systems that have only recently visible in global academic journals. The micro-level data suggest a delayed participation of social scientists and humanists in global science networks, with practical implications for predicting biological age from academic age. We calculate correlation coefficients, present contingency analysis of academic career stages with academic positions and age groups, and create a linear multivariate regression model. Our research suggests that in scientifically developing countries, academic age as a proxy for biological age should be used more cautiously than in advanced countries: ideally, it should be used only for STEMM disciplines.
This longitudinal study explores persistence in research productivity at the individual level over academic lifetime: can highly productive scientists maintain relatively high levels of productivity. We examined academic careers of 2326 Polish full professors, including their lifetime biographical and publication histories. We studied their promotions and publications between promotions (79,027 articles) over a 40-year period across 14 science, technology, engineering, mathematics, and medicine (STEMM) disciplines. We used prestige-normalized productivity in which more weight is given to articles in high-impact than in low-impact journals, recognizing the highly stratified nature of academic science. Our results show that half of the top productive assistant professors continued as top productive associate professors, and half of the top productive associate professors continued as top productive full professors (52.6% and 50.8%). Top-to-bottom and bottom-to-top transitions in productivity classes occurred only marginally. In logistic regression models, two powerful predictors of belonging to the top productivity class for full professors were being highly productive as assistant professors and as associate professors (increasing the odds, on average, by 179% and 361%). Neither gender nor age (biological or academic) emerged as statistically significant. Our findings have important implications for hiring policies: hiring high- and low-productivity scientists may have long-standing consequences for institutions and national science systems as academic scientists usually remain in the system for decades. The Observatory of Polish Science (100,000 scientists, 380,000 publications) and Scopus metadata on 935,167 Polish articles were used, showing the power of combining biographical registry data with structured Big Data in academic profession studies.
This longitudinal study explores persistence in research productivity over time. We examine the trajectories of the academic careers of 2,326 current full professors in 14 STEMM disciplines, studying their lifetime biographical histories and publication histories. Every full professor is compared in terms of productivity classes (top, middle, bottom) with their peers at earlier career stages. We used prestige-normalized productivity in which more weight is given to articles in high-impact than in low-impact journals, recognizing the highly stratified nature of academic science. Our results show that membership in top productivity classes is to a large extent determined by being in these classes earlier. Half of the current top productive full professors belonged to top productivity classes throughout their academic careers. Half of the top productive assistant professors continued as top productive associate professors, and half of the top productive associate professors continued as top productive full professors (52.6% and 50.8%). Top-to-bottom and bottom-to-top transitions in productivity classes occurred marginally. The combination of biographical and demographic data with raw Scopus publication data from the past 50 years (N=1 million) made it possible to assign all full professors retrospective to different productivity, promotion age, and promotion speed classes. In logistic regression models, two powerful predictors of belonging to the top productivity class for full professors were being highly productive as assistant professors and as associate professors (increasing the odds by 180% and 360%). Neither gender nor age (biological or academic) emerged as statistically significant. Hiring both low-productivity and high-productivity scientists may have long-standing consequences for institutions and the national science system: after entering the system and achieving job stability, scientists in Poland (where attrition is low) usually remain in the system for years, if not decades.
The paper presents an application of spatial microsimulation methods for generating a synthetic population to estimate personal income in Poland in 2011 using census tables and EU-SILC 2011 microdata set. The first section presents a research problem and a brief overview of modern estimation methods in application to small domains with particular emphasis on spatial microsimulation. The second section contains an overview of selected synthetic population generation methods. In the last section personal income estimation on NUTS 3 level is presented with special emphasis on the quality of estimates.
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