The idea that science is a pretty good example of a meritocracy seems well-supported from a superficial examination of the evidence. If you look at what people in the very fanciest of private universities (Ivey League schools, Stanford, and so on) can accomplish, it is pretty impressive. Compare them to the next level of fancy private university and the most highly ranked of public institutions (University of Michigan, University of Texas, and so on), and they are also impressive (but a bit less so). You can work your way down the prestige level to community colleges, where any research at all is rare. Thus, an incurious (and perhaps ideologically motivated) person might conclude that academia is pretty good at sorting individuals based upon their abilities. What is probably obvious to you, however, is that all of these institutions also vary in the resources that they provide to faculty.
The most relevant resources for conducting research are time and money. The most important resource for a beginning faculty is startup funding. This is not a signing bonus, but rather money that the institution pays themselves to support research, and can be used to purchase equipment and supplies, fund travel, and fund employees. Because each PI runs their own unique little science company (in a sense, at least) when they are at schools where research is required, some funding is required to be able to do research. And research is not cheap! At the top end of the scale, startup can exceed a million dollars. The most useful thing you can do with all of that money is hire a lab manager and a whole crew of postdocs for several years, who are already-trained researchers that can collect data, write papers, and even acquire more funding. Towards the middle of the startup scale are institutions that will give enough startup (maybe in the low hundreds of thousands) to purchase equipment and supplies, but maybe only have a little money for hiring postdocs or lab manager, probably for only a limited amount of time. Where I work at FIU fits into this category. Towards the low end of the scale, start up is probably just a few tens of thousands of dollars or less, which can purchase some cheaper equipment and supplies, but probably not support many employees. Some teaching focused colleges and community colleges do not have any startup funds, so faculty generally fund their research (if they are research-active) by building it into the curriculum. Obviously, faculty who can hire a lab manager and multiple PhD level researchers working under their supervision (not to mention any equipment that they would want) should be much more productive than someone who was given ten thousand dollars.
Another really important resource is time. At the most “elite” universities, faculty in the sciences may only teach one class per year or less, and they often have ample support in the form of teaching assistants for all of the tedious tasks such as grading and managing the online learning system (e.g. Canvas or D2L). I am at a public research-intensive university, and I teach a little bit more than one class a semester (including supervising a lab), and this does not include mentoring graduate and undergraduate students. This is still way less than I taught at Georgia Southern University, where I was teaching three classes per semester. I have colleagues that have taught at even more teaching-focused universities, where they taught four or five classes per semester, and sometimes the laboratories (which take three hours of your time per week, same as a lecture course) don’t count or count for less for the teaching load. On the teaching-intensive side of the spectrum are underfunded and very-teaching focused colleges and community colleges, where teaching can exceed even six classes per semester. The math is simple- the more time that you have to focus on research, the more you will be able to accomplish. In addition, teaching tends to fragment your day such that making headway on intellectually challenging tasks like analyses and writing is even harder.
Another factor that elite universities have is proximity to power and prestige. This means that there will be opportunities to connect with individual donors and private foundations that can provide resources to support research and scholarship. Accepting this kind of private money can be problematic if the donor or foundations are controversial or just straight-up evil, and several elite Ivey league institutions have recently been taken to task for accepting money from evil people. Regardless of the morality, there is simply more ways to connect with money to fund research at those institutions that are farther up the prestige ladder.
What is the point that I am trying to make? Well, I think the instinct is to assume that folks who end up being productive and influential have accomplished everything that they have because of their qualities, while in reality, what you are able to do in science is the interaction between innate and developed abilities and available resources. I am often more impressed by what people are able to do while at teaching focused institution, compared to those who have a lot of resources and can devote most of their time to research. Particularly at the administrative levels, people love to use statistical indices (number of papers, impact factor of journals, h-index) to evaluate scientists. But all of those indices scale with resources and time in the field. Perhaps a better approach is to more holistically try to evaluate the scope of research impact in the broader context of the professional role and institution.
The most relevant resources for conducting research are time and money. The most important resource for a beginning faculty is startup funding. This is not a signing bonus, but rather money that the institution pays themselves to support research, and can be used to purchase equipment and supplies, fund travel, and fund employees. Because each PI runs their own unique little science company (in a sense, at least) when they are at schools where research is required, some funding is required to be able to do research. And research is not cheap! At the top end of the scale, startup can exceed a million dollars. The most useful thing you can do with all of that money is hire a lab manager and a whole crew of postdocs for several years, who are already-trained researchers that can collect data, write papers, and even acquire more funding. Towards the middle of the startup scale are institutions that will give enough startup (maybe in the low hundreds of thousands) to purchase equipment and supplies, but maybe only have a little money for hiring postdocs or lab manager, probably for only a limited amount of time. Where I work at FIU fits into this category. Towards the low end of the scale, start up is probably just a few tens of thousands of dollars or less, which can purchase some cheaper equipment and supplies, but probably not support many employees. Some teaching focused colleges and community colleges do not have any startup funds, so faculty generally fund their research (if they are research-active) by building it into the curriculum. Obviously, faculty who can hire a lab manager and multiple PhD level researchers working under their supervision (not to mention any equipment that they would want) should be much more productive than someone who was given ten thousand dollars.
Another really important resource is time. At the most “elite” universities, faculty in the sciences may only teach one class per year or less, and they often have ample support in the form of teaching assistants for all of the tedious tasks such as grading and managing the online learning system (e.g. Canvas or D2L). I am at a public research-intensive university, and I teach a little bit more than one class a semester (including supervising a lab), and this does not include mentoring graduate and undergraduate students. This is still way less than I taught at Georgia Southern University, where I was teaching three classes per semester. I have colleagues that have taught at even more teaching-focused universities, where they taught four or five classes per semester, and sometimes the laboratories (which take three hours of your time per week, same as a lecture course) don’t count or count for less for the teaching load. On the teaching-intensive side of the spectrum are underfunded and very-teaching focused colleges and community colleges, where teaching can exceed even six classes per semester. The math is simple- the more time that you have to focus on research, the more you will be able to accomplish. In addition, teaching tends to fragment your day such that making headway on intellectually challenging tasks like analyses and writing is even harder.
Another factor that elite universities have is proximity to power and prestige. This means that there will be opportunities to connect with individual donors and private foundations that can provide resources to support research and scholarship. Accepting this kind of private money can be problematic if the donor or foundations are controversial or just straight-up evil, and several elite Ivey league institutions have recently been taken to task for accepting money from evil people. Regardless of the morality, there is simply more ways to connect with money to fund research at those institutions that are farther up the prestige ladder.
What is the point that I am trying to make? Well, I think the instinct is to assume that folks who end up being productive and influential have accomplished everything that they have because of their qualities, while in reality, what you are able to do in science is the interaction between innate and developed abilities and available resources. I am often more impressed by what people are able to do while at teaching focused institution, compared to those who have a lot of resources and can devote most of their time to research. Particularly at the administrative levels, people love to use statistical indices (number of papers, impact factor of journals, h-index) to evaluate scientists. But all of those indices scale with resources and time in the field. Perhaps a better approach is to more holistically try to evaluate the scope of research impact in the broader context of the professional role and institution.
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