Scientific productivity matters a lot these days since so much of both the needs and wants of human society are now yoked if not directly to science then to one of its inevitable outputs, technological innovation. In recent years, scientists, policy makers and governments have started tying themselves up in knots trying to figure out how to improve scientific productivity as one study after another shows it is falling. For example, a 2017 study by economists found an inverse relationship between the size of the academic scientific workforce and scientific productivity – assessed as new ideas – since the 1930s and likewise for industry since the 1970s ().
Obviously academia increasingly looks to have a gummed up works, with a handful enjoying the spoils in terms of disproportionate access to money, personnel and resources while the rest fight over the remaining scraps in a ferocious competition.
Specifically in biomedicine, this has led to an appalling waste of talent and resources, with unnecessary replication of effort and irreproducible results as cutting corners becomes inevitable. The resulting environment fosters groupthink while new ideas find it increasingly difficult to break through.
This is the result of a distorted picture that relies on arbitrary quantifiable metrics. Rather, society needs science both for innovation as well as maintenance, and overweening emphasis on the former while ignoring the latter has led science policy astray.
The post-WW II scientific enterprise in a nutshell
Since the end of WW II, the US has dominated science and while details may differ in individual countries, its scientific culture likewise dominates. That culture developed from a specific science policy framework first outlined byin a seminal and hugely influential report titled ‘Science – The Endless Frontier‘ ( ). This codified the central and permanent role of the US government in funding university research. As a result, the US scientific workforce grew and grew, first with record numbers of graduates and PhDs and beginning in the 1980s, with ever-ballooning numbers of post-docs ( ).
With so much money sloshing around, academic publishers capitalized on the opportunity to corner the market in mediating the need to credential and assess quantifiable scientific productivity and as a result, scientific journals mushroomed as well.
Applied research and industrial applications feed off of this academia-funding agency-scientific publisher driven pipeline.
This, more or less, is the situation in practically every country in the world today, a model that first emerged in the triumphant and unbelievably wealthy post-WW II US and was replicated elsewhere in subsequent decades.
The implied but unstated premise in discussions about scientific productivity is that science should advance faster if more money is thrown at it, more people become scientists as a result and publish more papers. However, where is the evidence that new ideas, which is how scientific productivity tends to be measured, can emerge at command, as if at the press of a button?
What if the problem isn’t its perceived drop but rather in how scientific productivity tends to be assessed in the first place? Overweening reliance on arbitrary quantifiable metrics could easily create a distorted picture. Maybe a different perhaps even optimistic picture would emerge from examining the issue using a more holistic approach, one that enables a decoupling of the function of science in generating new ideas from the scientific training needed to maintain and advance society technologically. As society moves further into a post-industrial era, it stands to reason that the functions of a scientifically trained workforce would likewise change.
Examined this way, two post-WW II changes went hand in hand and fueled each other’s growth,
- one, the need for a scientifically trained workforce in increasing sectors of the economy, and,
- two, science as a stable, reasonably well-paying career.
Increasing sectors of a technologically advancing society need scientifically trained personnel, a process that started with the Industrial Revolution itself. Newer kinds of jobs that didn’t exist in previous eras now require and absorb scientifically trained staff. New ideas aren’t necessarily the end goals of such jobs. Rather, they have become essential for maintaining a given society’s living standards. Thus society’s relatively recent technological advancements have created the opportunity for a scientific career at a scale that didn’t exist previously.
- Consider quality control in manufacturing – pharma, food, even cosmetics, to name just a few sectors. Rank and file of such scientific staff don’t necessarily need to come up with new ideas. Their primary focus is to monitor and maintain requisite quality.
- Maintaining modern lifestyles requires a scientifically trained workforce to monitor and maintain systems in an increasingly wider sphere of operations. Consider energy and water supply, and environmental monitoring, some obvious examples.
- Consider how healthcare has changed since just WW II. Any number of advanced technologies, imaging and molecular assays to name just a couple, are now de rigeur for diagnosis and treatment, and each requires specialized scientific training.
Scientifically trained people may need to publish papers initially for credentialing purposes but those who move on into positions that require their scientific training to maintain and monitor systems and procedures in increasingly wider sectors of the economy don’t need to do so.
Rather than monomaniacally measuring scientific productivity through the unnecessarily narrow pin hole of new ideas, policy makers should holistically assess the increasingly essential role of the scientific workforce in all sorts of sectors of society. Only doing so would enable the formulation of policies that support both scientific innovation as well as a properly trained scientific workforce that is increasingly necessary for society’s maintenance itself.
Productivity in academic science measured as output of new ideas has clearly become problematic in recent years. However, that may be largely or even entirely due to over-reliance on problematic quantifiable metrics that inculcate a distorted picture of the current role of science in society. If policy makers use such a distorted picture as the basis for formulating policy, any wonder single-minded investment in fostering new ideas doesn’t yield the desired outcome?
Clearly science is advancing, having become ever more indispensable to humankind as scientifically trained personnel become ever more essential for maintaining society, a process that occurred organically, unbidden and evidently invisibly, at least to the eyes of policy makers.
Where is the support for the monitoring and maintaining functions currently being performed throughout society by an increasingly larger number of scientifically trained workforce?
Here lies the critical gap in science policy. Many who enter the science sector move into such positions not through intent but willy-nilly. There is simply no career guidance throughout the entire scientific ecosystem based on the ground reality that there are lots more scientifically trained job seekers than there are jobs that focus solely on new ideas.
Such job seekers and society alike would be far better served if policy makers and academia realized society today needs both the innovation and maintenance functions that scientific training provides, and accordingly established policies to support both and not just the former.
As for new ideas, until someone proves they can be generated to order, using that as a benchmark for assessing overall scientific productivity is akin to mining for fools gold. Such an approach unnecessarily distorts the picture about the scientific workforce and crucially, leads policy makers dangerously astray. As a result, investment and outcome in science have become artificially decoupled.
1. Bloom, Nicholas, et al. Are ideas getting harder to find?. No. w23782. National Bureau of Economic Research, 2017.
3. The 2018 Science & Engineering Indicators published by the National Science Board (NSF).