Paper Summary
Title: New Facts and Data about Professors and their Research
Source: arXiv
Authors: Kyle Myers et al.
Published Date: 2023-12-05
Podcast Transcript
Hello, and welcome to Paper-to-Podcast, the show where we turn academic papers into digestible audio bites. Today, we're diving into the world of academia, not the one filled with elbow patches and chalk dust, but where the real action happens: in the paychecks and the research labs. Huddle up, scholars and laymen alike, as we explore new findings about professors and their research, money-making habits, and the life behind those tweed curtains.
Kyle Myers and colleagues recently took out their magnifying glasses and decided to look at the cold, hard numbers in a paper published on December 5, 2023, titled "New Facts and Data about Professors and their Research." Now, before you yawn and reach for that coffee cup, let me tell you, this is not your average academic snoozefest.
One spicy meatball from their findings is the jaw-dropping inequality in professors' earnings. It turns out, there's more disparity within their own fields than between different fields. So, while you thought your grass was greener, turns out Professor Smith is just using better fertilizer. But wait, it gets juicier. These professors tend to marry other high-earners, creating academic powerhouses that could probably fund a small space program.
Now, what's raking in the cash? Clinical work is where it's at, folks. Meanwhile, time spent teaching? Not so much. It's like the academic version of a rock band: the lead singer (research) gets all the glory, while the bass player (teaching) keeps the groove going unnoticed.
And get this: the traditional "publish or perish" mantra? It's not all it's cracked up to be. Output per year doesn't always mean you're the most productive professor on the block. Especially if you're on the non-tenure track, where you could be hustling twice as hard for half the credit.
Age and tenure status also play a role like a fine wine, professors get better with age, but they also start writing books and getting tangled in more administrative vines post-tenure. And if you're wondering why your professor is living life on the edge, it could be because they lean towards "Edison-like" applied research, which apparently attracts the Indiana Jones of academia.
These revelations come courtesy of a survey so broad, it could cover the academic Grand Canyon. Myers and the gang reached out to professors at about 150 research-intensive U.S. institutions. They asked all the nitty-gritty questions about ranks, tenure, weekly work hours, tasks, earnings sources, and the nature of their research. They even checked if professors were fibbing about their salaries by comparing the survey answers to publicly reported numbers. Talk about doing your homework!
Now, let's talk about the muscle of the study. The researchers' Herculean effort gives us a peek into the academic kitchen, showing us who's cooking the research stew and who's just sprinkling in the salt. They didn't just rely on gut feelings; they used machine learning techniques to sift through the data. It's like having a robot Sherlock Holmes on the case.
But every hero has a weakness, and this study's kryptonite could be the representativeness of its sample. Maybe they missed out on capturing the full landscape of the academic Avengers, especially those medical school professors who are often in a league of their own.
Despite these potential limitations, the implications of this study are like finding the golden snitch in academic policy-making. Universities could use these insights to create a Hogwarts where professors are rewarded for more than just waving their research wands. They could also encourage a bit more daring in the research arena, maybe even spark the next big eureka moment.
And for those policymakers out there, this paper isn't just a good read; it's a treasure map to understanding how the tenure system influences the mystical art of research and how to distribute the administrative load without turning professors into desk jockeys.
So there you have it, folks, an academic paper that doesn't just sit on a shelf looking pretty but actually tells us something about the wizards behind the university curtains. You can find this paper and more on the paper2podcast.com website.
Supporting Analysis
One fascinating discovery is the significant inequality in professors' earnings within their own fields compared to across different fields. This inequality persists at the household level because professors often marry similarly high-earning partners. Interestingly, tasks and sources of earnings can explain about half of the variations in professors' earnings. Clinical work has the highest earnings association, while time spent teaching doesn't significantly affect earnings. The study also uncovered that the traditional measure of productivity, output per year, doesn't always align with productivity per research hour due to varying time allocations, particularly for non-tenure-track professors. Moreover, professors' beliefs about the riskiness of their research are strongly linked to the time they spend fundraising, their personal risk-aversion, and whether their research is hypothesis-generating. Age and tenure status influence research focus, with older professors shifting from journal articles to books and experiencing a notable increase in administrative duties post-tenure, accounting for reduced research time. Lastly, the paper reveals that professors who lean towards applied, commercially-relevant research, which is more "Edison-like," often exhibit higher personal risk-taking tendencies.
The researchers conducted a comprehensive survey of professors at around 150 research-intensive U.S. higher education institutions. They gathered data on professorial compensation, time management, research activities, and perceptions of their research. The survey included questions about professors' ranks, tenure status, weekly work hours, tasks they perform, sources of their earnings, and the nature of their research. Socio-demographic information such as race, ethnicity, and household income was also collected. To ensure a broad view across the spectrum of academia, the survey was crafted with a "breadth over depth" philosophy. This allowed the researchers to shed light on areas often ignored by empirical studies. To compare respondents with the population, the team used data observable for both groups, like institutional funding from the National Science Foundation’s Higher Education R&D survey and individual grant and publication records from the Dimensions database. The survey also tested the truthfulness of respondents' answers by comparing self-reported salaries to publicly reported salaries for a subset of researchers. Additionally, they employed machine learning techniques like stability selection to identify predictors of certain behaviors, such as risk-taking in research. The data was then analyzed to understand the relationships and motivations behind academic researchers' behaviors and decisions.
The most compelling aspects of this research lie in its comprehensive examination of the intricacies of academic life, particularly focusing on professors at research-intensive institutions in the U.S. The study's strength is in its breadth, addressing a range of factors from compensation and time allocation to personal beliefs about research risk-taking and orientation toward applied or basic research. The researchers' commitment to understanding the variety of influences on professors' professional lives and their subsequent research productivity is evident and necessary for a nuanced view of academic dynamics. The study's methodology, employing a large-scale survey to gather data directly from professors, follows best practices by ensuring a representative sample across different fields and ranks, accounting for potential biases and non-response rates. The use of a survey allows for the collection of otherwise difficult-to-obtain data, such as personal risk-taking behaviors and time spent on various academic tasks. The researchers' efforts to link self-reported data to external databases for validation purposes demonstrate a rigorous approach to ensuring the accuracy of their findings. Additionally, providing a subset of the data for public access reflects a commitment to transparency and could encourage further research in this area.
One possible limitation of this survey-based research is the challenge of ensuring the representativeness of the sample. Despite efforts to test for representativeness, there may still be biases in the sample that could affect the generalizability of the findings. For instance, the study found an underrepresentation of professors from medical schools, which could skew results given that medical schools often have different structures and faculty responsibilities compared to other academic departments. Additionally, the survey is cross-sectional, which means it captures a single moment in time and may not fully account for changes over a professor's career or shifts in the academic environment. This could limit the study's ability to draw conclusions about temporal dynamics. Another limitation is the reliance on self-reported data, which can be subject to inaccuracies or biases, despite efforts to validate the data against publicly reported salaries. Furthermore, the study does not report causal effects, so while it can identify correlations, it cannot definitively establish cause-and-effect relationships between the observed factors and outcomes. Lastly, there may be important but unobserved variables that were not included in the survey, which could influence the results.
The research could have a range of applications in both academic policy-making and institutional management. By identifying factors that contribute to professors' productivity and earnings, universities could better design policies that promote effective time allocation and incentivize high-impact research. Understanding the variations in earnings and the relationship between research output and compensation could also inform salary structures to ensure equitable and competitive pay. Moreover, the findings regarding professors' perceptions of research risk and their personal risk aversion could be used to tailor grant-making processes, potentially encouraging more innovative and high-risk research projects. Insights into the life-cycle changes in professors' research focus could lead to more supportive environments for senior academics, facilitating their continued contribution to their fields. For policy-makers and higher education researchers, the study's results could provide empirical evidence to support discussions on the tenure system's impact on research productivity and the allocation of administrative duties. Additionally, the basic-applied research spectrum identified in the study could help in evaluating the impact of research and its alignment with industry or societal needs. Understanding these dynamics could lead to more informed decisions on funding allocation, research support services, and the development of interdisciplinary programs that bridge the gap between basic and applied research.