Alexander Martinez C

A recent study claimed that of 208 Nobel Prizes in Physiology or Medicine from 1901-2023, just 20 awardees thanked a mentor during the Lecture. This was surprising to me. So I scraped all Nobel Lectures, converted them into clean .txt files, and repeated the analysis. I extracted 525 lectures in all, with 145 from chemistry, 68 from economics, 158 from medicine, and 154 from physics. Next, I used the OCR tool from Datalab to extract just the text from each lecture while removing any images, captions, and references. Finally, I repeated the analysis. The study in question did a simple Ctrl+F for mentions of the word "mentor," (which is really just too simple for this kind of analysis). When I did the same, I found that just 12 of 158 (7.6%) Medicine lectures contain the word "mentor". I found similar or lower rates in other fields, with 11 of 145 (7.6%) Chemistry lectures, 7 of 154 (4.5%) Physics lectures, and 2 of 68 (2.9%) Economics lectures containing the word. But again, this method completely misses most acknowledgements. A winner who thanks “my students and colleagues,” like Mario Molina did in 1995, wouldn’t be counted at all. So next, I built a Python script that broadened the search to include words like mentor(s), student(s), and advisor(s). Using these criteria, nearly 90 percent of Chemistry, Physics, and Medicine lectures contained at least one of those terms, whereas just 3 of 68 in Economics did. Finally, I expanded my script to include spatial context. Specifically, this new script checked whether mentions of these keywords appeared near words indicative of gratitude, such as “thank,” “owe,” or “appreciate.” With this filter, I found that 38.1 percent of all Nobel lectures include a direct acknowledgment of someone else, and that this number is much higher in Medicine (more than 50 percent.) In other words, Nobel laureates thank their mentors and colleagues and students far more than this recent study may suggest. Thanks for coming to my TED talk.