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Credit: Rhoda Baer
A scientist’s chances of landing a faculty position at an academic institution are predictable based solely on his or her publication record, according to a study published in Current Biology.
Chances depend mostly on the number of publications the scientist has, the impact factor of the journals in which those papers are published, and the number of papers that receive more citations than expected based on the journal in which they were published, the researchers said.
“We’d like to start a discussion on what factors are taken into account when people are selected to become a principal investigator,” said study author David van Dijk, PhD, of the Weizmann Institute of Science in Rehovot, Israel.
“On the one hand, these results are encouraging, because they suggest that people are promoted based on merit. On the other hand, many of the most groundbreaking papers were not published in high-impact-factor journals and did not initially receive a high number of citations. This filtering method will certainly miss some phenomenal and ahead-of-their time scientists.”
Dr Van Dijk said he and his colleagues were motivated by endless conversations with fellow graduate students and post docs, who were dreaming of their first paper in a prestigious journal. There was the sense that those publications were the tickets to success.
So Dr van Dijk and his colleagues wanted to see if they could find evidence to that effect. And, indeed, they could.
The researchers generated publication record data for more than 25,000 scientists and used a machine-learning approach to generate a model of each individual’s chances of moving from the first-author position, typically reserved for trainees, to the last-author position, a place most often held by principal investigators (PIs).
“We find that whether or not a scientist becomes a PI is largely predictable by their publication record, even taking into account only the first few years of publication,” the researchers reported. “Our model is able to predict with relatively high accuracy who becomes a PI and is also able to predict how long this will take.”
To calculate your own likelihood of success using this model, visit: http://www.pipredictor.com.
Dr Van Dijk said the study results suggest the current system is working. Understanding how it works might be useful for those thinking through their careers or for those on hiring committees who might like to allow factors outside of the publication record to factor more significantly in hiring decisions.
The authors don’t recommend that scientists make decisions about their futures based solely on their PI prediction scores, of course. There are surely plenty of other harder-to-quantify factors that can also play a role. And there is some hopeful news for those who are persistent, even if they haven’t landed that stellar paper just yet.
“There is an element of luck in getting a paper in Nature, Cell, or Science, so it can be frustrating if you think you are a good scientist and want to succeed, but that high-impact-factor paper just doesn’t happen,” Dr van Dijk said.
“It’s encouraging that we find that doing good-quality science on a consistent basis—as evidenced by multiple first-author papers of reasonable impact factor—does seem to be rewarded in the end.” 
Credit: Rhoda Baer
A scientist’s chances of landing a faculty position at an academic institution are predictable based solely on his or her publication record, according to a study published in Current Biology.
Chances depend mostly on the number of publications the scientist has, the impact factor of the journals in which those papers are published, and the number of papers that receive more citations than expected based on the journal in which they were published, the researchers said.
“We’d like to start a discussion on what factors are taken into account when people are selected to become a principal investigator,” said study author David van Dijk, PhD, of the Weizmann Institute of Science in Rehovot, Israel.
“On the one hand, these results are encouraging, because they suggest that people are promoted based on merit. On the other hand, many of the most groundbreaking papers were not published in high-impact-factor journals and did not initially receive a high number of citations. This filtering method will certainly miss some phenomenal and ahead-of-their time scientists.”
Dr Van Dijk said he and his colleagues were motivated by endless conversations with fellow graduate students and post docs, who were dreaming of their first paper in a prestigious journal. There was the sense that those publications were the tickets to success.
So Dr van Dijk and his colleagues wanted to see if they could find evidence to that effect. And, indeed, they could.
The researchers generated publication record data for more than 25,000 scientists and used a machine-learning approach to generate a model of each individual’s chances of moving from the first-author position, typically reserved for trainees, to the last-author position, a place most often held by principal investigators (PIs).
“We find that whether or not a scientist becomes a PI is largely predictable by their publication record, even taking into account only the first few years of publication,” the researchers reported. “Our model is able to predict with relatively high accuracy who becomes a PI and is also able to predict how long this will take.”
To calculate your own likelihood of success using this model, visit: http://www.pipredictor.com.
Dr Van Dijk said the study results suggest the current system is working. Understanding how it works might be useful for those thinking through their careers or for those on hiring committees who might like to allow factors outside of the publication record to factor more significantly in hiring decisions.
The authors don’t recommend that scientists make decisions about their futures based solely on their PI prediction scores, of course. There are surely plenty of other harder-to-quantify factors that can also play a role. And there is some hopeful news for those who are persistent, even if they haven’t landed that stellar paper just yet.
“There is an element of luck in getting a paper in Nature, Cell, or Science, so it can be frustrating if you think you are a good scientist and want to succeed, but that high-impact-factor paper just doesn’t happen,” Dr van Dijk said.
“It’s encouraging that we find that doing good-quality science on a consistent basis—as evidenced by multiple first-author papers of reasonable impact factor—does seem to be rewarded in the end.”
Credit: Rhoda Baer
A scientist’s chances of landing a faculty position at an academic institution are predictable based solely on his or her publication record, according to a study published in Current Biology.
Chances depend mostly on the number of publications the scientist has, the impact factor of the journals in which those papers are published, and the number of papers that receive more citations than expected based on the journal in which they were published, the researchers said.
“We’d like to start a discussion on what factors are taken into account when people are selected to become a principal investigator,” said study author David van Dijk, PhD, of the Weizmann Institute of Science in Rehovot, Israel.
“On the one hand, these results are encouraging, because they suggest that people are promoted based on merit. On the other hand, many of the most groundbreaking papers were not published in high-impact-factor journals and did not initially receive a high number of citations. This filtering method will certainly miss some phenomenal and ahead-of-their time scientists.”
Dr Van Dijk said he and his colleagues were motivated by endless conversations with fellow graduate students and post docs, who were dreaming of their first paper in a prestigious journal. There was the sense that those publications were the tickets to success.
So Dr van Dijk and his colleagues wanted to see if they could find evidence to that effect. And, indeed, they could.
The researchers generated publication record data for more than 25,000 scientists and used a machine-learning approach to generate a model of each individual’s chances of moving from the first-author position, typically reserved for trainees, to the last-author position, a place most often held by principal investigators (PIs).
“We find that whether or not a scientist becomes a PI is largely predictable by their publication record, even taking into account only the first few years of publication,” the researchers reported. “Our model is able to predict with relatively high accuracy who becomes a PI and is also able to predict how long this will take.”
To calculate your own likelihood of success using this model, visit: http://www.pipredictor.com.
Dr Van Dijk said the study results suggest the current system is working. Understanding how it works might be useful for those thinking through their careers or for those on hiring committees who might like to allow factors outside of the publication record to factor more significantly in hiring decisions.
The authors don’t recommend that scientists make decisions about their futures based solely on their PI prediction scores, of course. There are surely plenty of other harder-to-quantify factors that can also play a role. And there is some hopeful news for those who are persistent, even if they haven’t landed that stellar paper just yet.
“There is an element of luck in getting a paper in Nature, Cell, or Science, so it can be frustrating if you think you are a good scientist and want to succeed, but that high-impact-factor paper just doesn’t happen,” Dr van Dijk said.
“It’s encouraging that we find that doing good-quality science on a consistent basis—as evidenced by multiple first-author papers of reasonable impact factor—does seem to be rewarded in the end.”