Can we agree that Albert Einstein was a scientist? That he was a good one (in fact, a great one)? And that his scientific work has been immeasurably influential?
I’m asking these silly questions for a couple of reasons. One: Einstein would, in the present competitive academic environment, have a really hard time getting recognized as a scientist of some stature. He worked in a marginal branch of science – more on this in a moment – and the small oeuvre he published (another critical limitation now) was not written in English but in German. His classic articles bore titles such as “Die vom Relativätsprinzip geforderte Trägheit der Energie” and appeared in journals called “Annalen der Physik” or “Beiblätter zu den Annalen der Physik”. Nobody would read such papers nowadays.
Two, his work was purely theoretical. That means that it revolved around the production of new ideas, or to put it more bluntly, around imagination. These forms of imagination were not wild or unchecked – it wasn’t “anything goes”. They were based on a comprehensive knowledge of the field in which he placed these ideas (the “known facts of science”, one could say, or “the state of the art” in contemporary jargon ), and the ideas themselves presented a synthesis, sweeping up what was articulated in fragmentary form in various sources and patching up the gaps between the different fragments. His ideas, thus, were imagined modes of representation of known facts and new (unknown but hypothetical and thus plausible or realistic) relations between them.
There was nothing “empirical” about his work. In fact, it took decades before aspects of his theoretical contributions were supported by empirical evidence, and other aspects still await conclusive empirical proof. He did not construct these ideas in the context of a collaborative research project funded by some authoritative research body – he developed them in a collegial dialogue with other scientists, through correspondence, reading and conversation. In the sense of today’s academic regime, there was, thus, nothing “formal”, countable, measurable, structured, justifiable, or open to inspection to the way he worked. The practices that led to his theoretical breakthroughs would be all but invisible on today’s worksheets and performance assessment forms.
As for “method”, the story is even more interesting. Einstein would rather systematically emphasize the disorderly, even chaotic nature of his work procedures, and mention the fact (often also confirmed by witnesses) that, when he got stuck, he would leave his desk, papers and notebooks, pick up his violin and play music until the crucial brainwave occurred. He was a supremely gifted specialized scholar, of course, but also someone deeply interested (and skilled) in music, visual art, philosophy, literature and several other more mundane (and “unscientific”) fields. His breakthroughs, thus, were not solely produced by advances in the methodical disciplinary technique he had developed; they were importantly triggered by processes that were explicitly non-methodical and relied on “stepping out” of the closed universe of symbolic practices that made up his science.
Imagine, now, that we would like to train junior scholars to become new Einsteins. How would we proceed? Where would we start?
Those familiar with contemporary research training surely know what I am talking about: students are trained to become “scientists” by doing the opposite of what turned Einstein into the commanding scientist he became. The focus these days is entirely – and I am not overstating this – on the acquisition, development and refining of methods to be deployed on problems which in turn are grounded in assumptions by means of hypotheses. Research training now is the training of practicing that model. The problems are defined by the assumptions and discursively formulated through the hypotheses – so they tolerate little reflection or unthinking, they are to be adopted. And what turns the student’s practices into “science” is the disciplined application of acquired methods to such problems resting on such assumptions. This, then, yields scientific facts either confirming or challenging the “hypotheses” that guided the research, and the production of such facts-versus-hypotheses is called scientific research. Even more: increasingly we see that only this procedure is granted the epithet of “scientific” research.
The stage in which ideas are produced is entirely skipped. Or better, the tactics, practices and procedures for constructing ideas are eliminated from research training. The word “idea” itself is often pronounced almost with a sense of shame, as an illegitimate and vulgar term better substituted by formal jargonesque (but equally vague) terms such as “hypothesis”. While, in fact, the closest thing to “idea” in my formulation is the term “assumption” I used in my description of the now dominant research model. And the thing is that while we train students to work from facts through method to hypotheses in solving a “problem”, we do not train them to questions the underlying assumptions that formed both the “problem” they intend to address and the epistemological and methodological routes designed to solve such problems. To put it more sharply, we train them in accepting a priori the fundamental issues surrounding and defining the very stuff they should inquire into and critically question: the object of research, its relations with other objects, the “evidence” we shall accept as elements adequately constructing this object, and the ways in which we can know, understand and communicate all this. We train them, thus, in reproducing – and suggestively confirming – the validity of the assumptions underlying their research.
“Assumptions” typically should be statements about reality, about the fundamental nature of phenomena as we observe and investigate them among large collectives of scientists. Thus, an example of an assumption could be “humans produce meaning through the orderly grammatical alignment of linguistic forms”. Or: “social groups are cohesive when they share fundamental values, that exist sociocognitively in members’ minds”. Or “ethnicity defines and determines social behavior”. One would expect such assumptions to be the prime targets of continuous critical reassessment in view (precisely) of the “facts” accumulated on aspects that should constitute them. After all, Einstein’s breakthroughs happened at the level of such assumptions, if you wish. Going through recent issues of several leading journals, however, leads to a perplexing conclusion: assumptions are nearly always left intact. Even more: they are nearly always confirmed and credentialed by accumulated “facts” from research – if so much research can be based on them, they must be true, so it seems. “Proof” here is indirect and by proxy, of course – like miracles “proving” the sacred powers of an invoked Saint.
Such assumptions effectively function not as statements about the fundamental nature of objects of research, open for empirical inspection and critique, but as axiomatic theses to be “believed” as a point of departure for research. Whenever such assumptions are questioned, even slightly, the work that does so is instantly qualified as “controversial” (and, in informal conversations, as “crackpot science” or “vacuous speculation”). And “re-search”, meaning “searching again”, no longer means searching again da capo, from step 1, but searching for more of the same. The excellent execution of a method and its logic of demonstration is presented as conclusive evidence for a particular reality. Yes, humans do indeed produce meaning through the orderly grammatical alignment of linguistic forms, because my well-crafted application of a method to data does not contradict that assumption. The method worked, and the world is chiseled accordingly.
Thus we see that the baseline intellectual attitude of young researchers, encouraged or enforced and positively sanctioned – sufficient, for instance, to obtain a doctoral degree and get your work published in leading journals, followed by a ratified academic career – is one in which accepting and believing are key competences, increasingly even the secret of success as a researcher. Not unthinking the fundamental issues in one’s field, and abstaining from a critical inquisitive reflex in which one looks, unprompted, for different ways of imagining objects and relations between them, eventually arriving at new, tentative assumptions (call them ideas now) – is seen as being “good” as a researcher.
The reproductive nature of such forms of research is institutionally supported by all sorts of bonuses. Funding agencies have a manifest and often explicit preference for research that follows the clear reproductive patterns sketched above. In fact, funding bodies (think of the EU) often provide the fundamental assumptions themselves and leave it to researchers to come up with proof of their validity. Thus, for instance, the EU would provide in its funding calls assumptions such as “security risks are correlated with population structure, i.e. with ethnocultural and religious diversity” and invite scientific teams to propose research within the lines of defined sociopolitical reality thus drawn. Playing the game within these lines opens opportunities to acquire that much-coveted (and institutionally highly rewarded) external research funding – an important career item in the present mode of academic politics.
There are more bonuses. The reproductive nature of such forms of research also ensures rapid and high-volume streams of publications. The work is intellectually extraordinarily simple, really, even if those practicing it will assure us that it is exceedingly hard: no fundamental (and often necessarily slow) reflection, unthinking and imaginative rethinking are required, just the application of a standardized method to new “problems” suffices to achieve something that can qualify as (new or original) scientific fact and can be written down as such. Since literature reviews are restricted to reading nothing fundamentally questioning the assumptions, but reading all that operates within the same method-problem sphere, published work quickly gains high citation metrics, and the journals carrying such work are guaranteed high impact factors – all, again, hugely valuable symbolic credit in today’s academic politics. Yet, reading such journal issues in search for sparkling and creative ideas usually turns into a depressing confrontation with intellectual aridity. I fortunately can read such texts as a discourse analyst, which makes them at least formally interesting to me. But that is me.
Naturally, but unhappily, nothing of what I say here is new. It is worth returning to that (now rarely consulted) classic by C. Wright Mills, “The Sociological Imagination” (1959) to get the historical perspective right. Mills, as we know, was long ago deeply unhappy with several tendencies in US sociology. One tendency was the reduction of science to what he called “abstracted empiricism” – comparable to the research model I criticized here. Another was the fact that this abstracted empiricism took the “grand theory” of Talcott Parsons for granted as assumptions in abstracted empirical research. A poor (actually silly) theory vulnerable to crippling empirical criticism, Mills complained, was implicitly confirmed by the mass production of specific forms of research that used the Parsonian worldview as an unquestioned point of departure. The title of his book is clear: in response to that development, Mills strongly advocated imagination in the sense outline earlier, the fact that the truly creative and innovative work in science happens when scientists review large amounts of existing “known facts” and reconfigure them into things called ideas. Such re-imaginative work – I now return to a contemporary vocabulary – is necessarily “slow science” (or at least slower science), and is effectively discouraged in the institutional systems of academic valuation presently in place. But those who neglect, dismiss or skip it do so at their own peril, C. Wright Mills insisted.
It is telling that the most widely quoted scholars tend to be people who produced exactly such ideas and are labeled as “theorists” – think of Darwin, Marx, Foucault, Freud, Lévi-Strauss, Bourdieu, Popper, Merleau-Ponty, Heidegger, Hayek, Hegel and Kant. Many of their most inspiring works were nontechnical, sweeping, bold and provocative – “controversial” in other words, and open to endless barrages of “method”-focused criticism. But they influenced, and changed, so much of the worldviews widely shared by enormous communities of people worldwide and across generations.
It is worth remembering that such people did really produce science, and that very often, they changed and innovated colossal chunks of it by means of ideas, not methods. Their ideas have become landmarks and monuments of science (which is why everyone knows Einstein but only very few people know the scientists who provided empirical evidence for his ideas). It remains worthwhile examining their works with students, looking closely at the ways in which they arrived at the ideas that changed the world as we know it. And it remains imperative, consequently, to remind people that dismissing such practices as “unscientific” – certainly when this has effects on research training – denies imperious scientific efforts, inspiring and forming generations of scientists, the categorical status of “science”, reserving it for a small fraction of scientific activities which could, perhaps far better, be called “development” (as in “product development”). Whoever eliminates ideas from the semantic scope of science demonstrates a perplexing lack of them. And whoever thinks that scientific ideas are the same as ideas about where to spend next year’s holiday displays a tremendous lack of familiarity with science.
Much of what currently dominates the politics and economies of science (including how we train young scientists) derives its dominant status not from its real impact on the world of knowledge but from heteronomic forces operating on the institutional environments for science. The funding structure, the rankings, the metrics-based appraisals of performance and quality, the publishing industry cleverly manipulating all that – those are the engines of “science” as we now know it. These engines have created a system in which Albert Einstein would be reduced to a marginal researcher – if a researcher at all. If science is supposed to maintain, and further develop, the liberating and innovative potential it promised the world since the era of Enlightenment, it is high time to start questioning all that, for an enormous amount of what now passes as science is astonishingly banal in its purpose, function and contents, confirming assumptions that are sometimes simply absurd and surreal.
We can start by talking to the young scholars we train about the absolutely central role of ideas in scientific work, encourage them to abandon the sense of embarrassment they experience whenever they express such ideas, and press upon them that doing scholarly work without the ambition to continue producing such ideas is, at best, a reasonably interesting pastime but not science.