According to 55 percent of 350,000 people from 70 countries who participated online in Richard Wiseman’s Laugh Lab experiment (discussed in last month’s column), this is the world’s funniest joke:

Two hunters are out in the woods when one of them collapses. He doesn’t seem to be breathing, and his eyes are glazed. The other guy whips out his phone and calls the emergency services. He gasps, “My friend is dead! What can I do?” The operator says, “Calm down. I can help. First, let’s make sure he’s dead.” There is a silence, then a shot is heard. Back on the phone, the guy says, “Okay, now what?”

So say the data, but according to Wiseman’s personal narrative describing how the research was actually conducted (in his new book Quirkology), he believes that “we uncovered the world’s blandest joke — the gag that makes everyone smile but very few laugh out loud. But as with so many quests, the journey was far more important than the destination. Along the way we looked at what makes us laugh, how laughter can make you live longer, how humor should unite different nations, and we discovered the world’s funniest comedy animal.” Chickens notwithstanding, such first-person accounts in popular science books that include the journey and not just the destination afford readers a glimpse into how science is really carried out.

Formal science writing — what I call the “narrative of explanation” — presents a neat and tidy step-by-step process of Introduction- Methods-Results-Discussion, grounded in a nonexistent “scientific method” of Observation- Hypothesis-Prediction- Experiment followed in a linear fashion. This type of science writing is like autobiography, and as the comedian Stephen Wright said, “I’m writing an unauthorized autobiography.” Any other kind is fiction. Formal science writing is like Whiggish history — the conclusion draws the explanation toward it, forcing facts and events to fall neatly into a causal chain where the final outcome is an inevitable result of a logical and inevitable sequence.

Informal science writing — what I call the “narrative of practice” — presents the actual course of science as it is interwoven with periodic insights and subjective intuitions, random guesses and fortuitous findings. Science, like life, is messy and haphazard, full of quirky contingencies, unexpected bifurcations, serendipitous discoveries, unanticipated encounters and unpredictable outcomes. This chaotic process helps to explain, in part, the phenomenal success in recent decades of first-person popular accounts by scientists of how they actually did their research. The effect is especially noteworthy in works exploring the peculiarities of life.

Steven Levitt’s and Stephen Dubner’s Freakonomics (William Morrow, 2006) illuminates the power of incentives through certain oddities. For instance, that most drug dealers live with their mothers because only the top guys make the big bucks while the rest bide their time and pay their dues or that baby names tell us about the motives of parents. Cornell University professor Robert Frank’s The Economic Naturalist: In Search of Explanations for Everyday Enigmas (Basic, 2007) employs the principle of costbenefit analysis to explain such idiosyncrasies as why drive-up ATM keypads have Braille dots (because it is cheaper to make the same machine for both drive-up and walk-up locations), why brown eggs are more expensive than white eggs (because there is less demand and the hens that lay them are larger and consume more food), why it is harder to find a taxi in the rain (because more people use them when it is raining, most cabbies reach their fare goals earlier in the day), and why milk is stored in rectangular cartons but soft drinks come in round cans (because it is handier to drink soda directly from a round can but easier to pour and store milk in a rectangular carton).

In my October column I railed against the artificial (and odious) ranking of technical science writing over popular science writing. I suggested that the latter should be elevated to a more exalted standing of “integrative science,” where good science writing integrates data, theory and narrative into a useful and compelling work. Here I add that exploring the minutiae of life, especially on the quirky borderlands of science, makes the scientific process more accessible to everyone. Where a narrative of explanation might read something like “the data lead me to conclude…,” a narrative of practice reads more like “Huh, that’s weird…”

Weirdness trumps data in the biography of science.

Over the past three decades I have noted two disturbing tendencies in both science and society: first, to rank the sciences from “hard” (physical sciences) to “medium” (biological sciences) to “soft” (social sciences); second, to divide science writing into two forms, technical and popular. And, as such rankings and divisions are wont to do, they include an assessment of worth, with the hard sciences and technical writing respected the most, and the soft sciences and popular writing esteemed the least. Both these prejudices are so far off the mark that they are not even wrong.

I have always thought that if there must be a rank order (which there mustn’t), the current one is precisely reversed. The physical sciences are hard, in the sense that calculating differential equations is difficult, for example. The variables within the causal net of the subject matter, however, are comparatively simple to constrain and test when contrasted with, say, computing the actions of organisms in an ecosystem or predicting the consequences of global climate change. Even the difficulty of constructing comprehensive models in the biological sciences pales in comparison to that of modeling the workings of human brains and societies. By these measures, the social sciences are the hard disciplines, because the subject matter is orders of magnitude more complex and multifaceted.

Between technical and popular science writing is what I call “integrative science,” a process that blends data, theory and narrative. Without all three of these metaphorical legs, the seat on which the enterprise of science rests would collapse. Attempts to determine which of the three legs has the greatest value is on par with debating whether Π or r² is the most important factor in computing the area of a circle.

Consider data and theory first. I began this column in April 2001 with what I called “Darwin’s dictum,” which came from a quote from the sage of Down in response to a critique that On the Origin of Species was too theoretical and that he should have just “put his facts before us and let them rest.” Darwin responded by explaining the proper relation between data and theory: “About thirty years ago there was much talk that geologists ought only to observe and not theorize, and I well remember someone saying that at this rate a man might as well go into a gravel-pit and count the pebbles and describe the colours. How odd it is that anyone should not see that all observation must be for or against some view if it is to be of any service!”

Charles Darwin’s dictum holds that if observations are to be of any use they must be tested against some view — a thesis, model, hypothesis, theory or paradigm. The facts that we measure or perceive never just speak for themselves but must be interpreted through the colored lenses of ideas. Percepts need concepts, and vice versa. We can no more separate our theories and concepts from our data and percepts than we can find a true Archimedean point — a god’s-eye view — of ourselves and our world.

Data and theory are not enough. As primates, humans seek patterns and establish concepts to understand the world around us, and then we describe it. We are storytellers. If you cannot tell a good story about your data and theory — that is, if you cannot explain your observations, what view they are for or against and what service your efforts provide — then your science is incomplete. The view of science as primary research published in the peer-reviewed sections of journals only, with everything else relegated to “mere popularization,” is breathtakingly narrow and naive. Were this restricted view of science true, it would obviate many of the greatest works in the history of science, from Darwin’s On the Origin of Species to Jared Diamond’s Guns, Germs, and Steel, the evolutionary biologist’s environmental theory about the differential rates of development of civilizations around the world for the past 13,000 years.

Well-crafted narratives by such researchers as Richard Dawkins, Steven Pinker, the late Stephen Jay Gould and many others are higher-order works of science that synthesize and coalesce primary sources into a unifying whole toward the purpose of testing a general theory or answering a grand question. Integrative science is hard science.