Dataset Information

Persistence and uncertainty in the academic career.

ABSTRACT: Understanding how institutional changes within academia may affect the overall potential of science requires a better quantitative representation of how careers evolve over time. Because knowledge spillovers, cumulative advantage, competition, and collaboration are distinctive features of the academic profession, both the employment relationship and the procedures for assigning recognition and allocating funding should be designed to account for these factors. We study the annual production n(i)(t) of a given scientist i by analyzing longitudinal career data for 200 leading scientists and 100 assistant professors from the physics community. Our empirical analysis of individual productivity dynamics shows that (i) there are increasing returns for the top individuals within the competitive cohort, and that (ii) the distribution of production growth is a leptokurtic "tent-shaped" distribution that is remarkably symmetric. Our methodology is general, and we speculate that similar features appear in other disciplines where academic publication is essential and collaboration is a key feature. We introduce a model of proportional growth which reproduces these two observations, and additionally accounts for the significantly right-skewed distributions of career longevity and achievement in science. Using this theoretical model, we show that short-term contracts can amplify the effects of competition and uncertainty making careers more vulnerable to early termination, not necessarily due to lack of individual talent and persistence, but because of random negative production shocks. We show that fluctuations in scientific production are quantitatively related to a scientist's collaboration radius and team efficiency.

SUBMITTER: Petersen AM

PROVIDER: S-EPMC3325726 | biostudies-literature | 2012 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Persistence and uncertainty in the academic career.

Petersen Alexander M AM Riccaboni Massimo M Stanley H Eugene HE Pammolli Fabio F

Proceedings of the National Academy of Sciences of the United States of America 20120319 14

Understanding how institutional changes within academia may affect the overall potential of science requires a better quantitative representation of how careers evolve over time. Because knowledge spillovers, cumulative advantage, competition, and collaboration are distinctive features of the academic profession, both the employment relationship and the procedures for assigning recognition and allocating funding should be designed to account for these factors. We study the annual production n(i) ...[more]

PMID: 22431620

Similar Datasets

Project description:ObjectivesTo review systematically the evidence about what factors influence the decision to choose or not choose a career in academic medicine.DesignA systematic review of relevant literature from 1990 to May 2005.Data sourcesSearches of The Cochrane Library, Medline (using Ovid and PubMed) from 1990 to May 2005, and EMBASE from 1990 to May 2005 were completed to identify relevant studies that explored the influential factors. Additional articles were identified from searching the bibliographies of retrieved articles.Selection of studiesWe attempted to identify studies that included residents, fellows, or staff physicians. No restrictions were placed on the study methodologies identified and all articles presenting empirical evidence were retrieved. For cohort, case-control, and cross-sectional studies, minimum inclusion criteria were the presence of defined groups, and the ability to extract relevant data. For surveys that involved case series, minimum inclusion criteria were a description of the population, and the availability of extractable data. Minimum inclusion criteria for qualitative studies were descriptions of the sampling strategy and methods.ResultsThe search identified 251 abstracts; 25 articles were included in this review. Completion of an MD with a graduate degree or fellowship program is associated with a career in academic medicine. Of the articles identified in this review, this finding is supported by the highest quality of evidence. Similarly, the completion of research and publication of this research in medical school and residency are associated with a career in academic medicine. The desire to teach, conduct research, and the intellectual stimulation and challenge provided in academia may also persuade people to choose this career path. The influence of a role model or a mentor was reported by physicians to impact their decision making. Trainees' interest in academic medicine wanes as they progress through their residency.ConclusionsIn order to revitalize academic medicine, we must engage trainees and retain their interest throughout their training. Research opportunities for medical students, and fellowships or graduate training can meet this challenge and influence career choice. Initiatives to stimulate and maintain interest in academic medicine should be evaluated in prospective studies across multiple sites.

Project description:BackgroundFor students entering a science PhD program, a tenure-track faculty research position is often perceived as the ideal long-term goal. A relatively small percentage of individuals ultimately achieve this goal, however, with the vast majority of PhD recipients ultimately finding employment in industry or government positions. Given the disparity between academic career ambitions and outcomes, it is useful to understand factors that may predict those outcomes. Toward this goal, the current study examined employment status of PhD graduates from biomedical sciences programs at the University of Colorado Anschutz Medical Campus (CU AMC) and related this to metrics of predoctoral publication records, as well as to other potentially important factors, such as sex and time-since-degree, to determine if these measures could predict career outcomes.MethodsDemographic information (name, PhD program, graduation date, sex) of CU AMC biomedical sciences PhD graduates between 2000 and 2015 was obtained from University records. Career outcomes (academic faculty vs. non-faculty) and predoctoral publication records (number and impact factors of first-author and non-first-author publications) were obtained via publicly available information. Relationships between predoctoral publication record and career outcomes were investigated by (a) comparing faculty vs. non-faculty publication metrics, using t-tests, and (b) investigating the ability of predoctoral publication record, sex, and time-since-degree to predict career outcomes, using logistic regression.ResultsSignificant faculty vs. non-faculty differences were observed in months since graduation (p < 0.001), first-author publication number (p = 0.001), average first-author impact factor (p = 0.006), and highest first-author impact factor (p = 0.004). With sex and months since graduation as predictors of career outcome, the logistic regression model was significant (p < 0.001), with both being male and having more months since graduation predicting career status. First-author related publication metrics (number of publications, average impact factor, highest impact factor) all significantly improved model fit (χ2 < 0.05 for all) and were all significant predictors of faculty status (p < 0.05 for all). Non-first-author publication metrics did not significantly improve model fit or predict faculty status.DiscussionResults suggest that while sex and months since graduation also predict career outcomes, a strong predoctoral first-author publication record may increase likelihood of obtaining an academic faculty research position. Compared to non-faculty, individuals employed in faculty positions produced more predoctoral first-author publications, with these being in journals with higher impact factors. Furthermore, first-author publication record, sex, and months since graduation were significant predictors of faculty status.

Dataset Information

Persistence and uncertainty in the academic career.

Publications

Persistence and uncertainty in the academic career.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure