  The catch-up effect and the Matthew effect offer opposing characterizations
of globalization: the former predicts an eventual convergence as the poor can
grow faster than the rich due to free exchanges of complementary resources,
while the latter, a deepening inequality between the rich and the poor. To
understand these effects on the globalization of research, we conduct an
in-depth study based on scholarly and patent publications covering STEM
research from 218 countries/regions over the past four decades, covering more
than 55 million scholarly articles and 1.7 billion citations. Unique to this
investigation is the simultaneous examination of both the research output and
its impact in the same data set, using a novel machine learning based measure,
called saliency, to mitigate the intrinsic biases in quantifying the research
impact. The results show that the two effects are in fact co-occurring: there
are clear indications of convergence among the high income and upper middle
income countries across the STEM fields, but a widening gap is developing that
segregates the lower middle and low income regions from the higher income
regions. Furthermore, the rate of convergence varies notably among the STEM
sub-fields, with the highly strategic area of Artificial Intelligence (AI)
sandwiched between fields such as Medicine and Materials Science that occupy
the opposite ends of the spectrum. The data support the argument that a leading
explanation of the Matthew effect, namely, the preferential attachment theory,
can actually foster the catch-up effect when organizations from lower income
countries forge substantial research collaborations with those already
dominant. The data resoundingly show such collaborations benefit all parties
involved, and a case of role reversal can be seen in the Materials Science
field where the most advanced signs of convergence are observed.
