Sadly, the hypothesis described below is very plausible.
The exception being that new tools or technological breakthroughs, especially those that can be validated relatively easily (e.g., by individual investigators or small labs), may still spread rapidly due to local incentives. CRISPR and Deep Learning are two good examples.
New theoretical ideas and paradigms have a much harder time in large fields dominated by mediocre talents: career success is influenced more by social dynamics than by real insight or capability to produce real results.
Johan S. G. Chu and James A. Evans
PNAS October 12, 2021 118 (41) e2021636118
Significance The size of scientific fields may impede the rise of new ideas. Examining 1.8 billion citations among 90 million papers across 241 subjects, we find a deluge of papers does not lead to turnover of central ideas in a field, but rather to ossification of canon. Scholars in fields where many papers are published annually face difficulty getting published, read, and cited unless their work references already widely cited articles. New papers containing potentially important contributions cannot garner field-wide attention through gradual processes of diffusion. These findings suggest fundamental progress may be stymied if quantitative growth of scientific endeavors—in number of scientists, institutes, and papers—is not balanced by structures fostering disruptive scholarship and focusing attention on novel ideas.
Abstract In many academic fields, the number of papers published each year has increased significantly over time. Policy measures aim to increase the quantity of scientists, research funding, and scientific output, which is measured by the number of papers produced. These quantitative metrics determine the career trajectories of scholars and evaluations of academic departments, institutions, and nations. Whether and how these increases in the numbers of scientists and papers translate into advances in knowledge is unclear, however. Here, we first lay out a theoretical argument for why too many papers published each year in a field can lead to stagnation rather than advance. The deluge of new papers may deprive reviewers and readers the cognitive slack required to fully recognize and understand novel ideas. Competition among many new ideas may prevent the gradual accumulation of focused attention on a promising new idea. Then, we show data supporting the predictions of this theory. When the number of papers published per year in a scientific field grows large, citations flow disproportionately to already well-cited papers; the list of most-cited papers ossifies; new papers are unlikely to ever become highly cited, and when they do, it is not through a gradual, cumulative process of attention gathering; and newly published papers become unlikely to disrupt existing work. These findings suggest that the progress of large scientific fields may be slowed, trapped in existing canon. Policy measures shifting how scientific work is produced, disseminated, consumed, and rewarded may be called for to push fields into new, more fertile areas of study.
A toy model of the dynamics of scientific research, with probability distributions for accuracy of experimental results, mechanisms for updating of beliefs by individual scientists, crowd behavior, bounded cognition, etc. can easily exhibit parameter regions where progress is limited (one could even find equilibria in which most beliefs held by individual scientists are false!). Obviously the complexity of the systems under study and the quality of human capital in a particular field are important determinants of the rate of progress and its character.
In physics it is said that successful new theories swallow their predecessors whole. That is, even revolutionary new theories (e.g., special relativity or quantum mechanics) reduce to their predecessors in the previously studied circumstances (e.g., low velocity, macroscopic objects). Swallowing whole is a sign of proper function -- it means the previous generation of scientists was competent: what they believed to be true was (at least approximately) true. Their models were accurate in some limit and could continue to be used when appropriate (e.g., Newtonian mechanics).
In some fields (not to name names!) we don't see this phenomenon. Rather, we see new paradigms which wholly contradict earlier strongly held beliefs that were predominant in the field* -- there was no range of circumstances in which the earlier beliefs were correct. We might even see oscillations of mutually contradictory, widely accepted paradigms over decades.
It takes a serious interest in the history of science (and some brainpower) to determine which of the two regimes above describes a particular area of research. I believe we have good examples of both types in the academy.
* This means the earlier (or later!) generation of scientists in that field was incompetent. One or more of the following must have been true: their experimental observations were shoddy, they derived overly strong beliefs from weak data, they allowed overly strong priors to determine their beliefs.