How a Story Rises

Notes on working in Science Storytelling

In 1881, Albert A. Michelson and Edward Morley had constructed an instrument of exquisite sensitivity for its time: an interferometer designed to detect the Earth's motion through the hypothesized luminiferous aether. Light beams were split, reflected along perpendicular paths, and recombined, their interference pattern expected to betray a subtle drift, evidence of an invisible medium long assumed to exist.The apparatus delivered none.

Today, the Michelson–Morley experiment is told as a prelude to Einstein's relativity, a necessary negation that cleared the ground for a new physics. But at the time, it was simply: a non-story, a non-event.

Half a century earlier, another scientific journey began under circumstances no less contingent. When Charles Darwin boarded the HMS Beagle in 1831, he did not do so as a professional scientist, nor even as the expedition's official naturalist. He was invited aboard as a "gentleman companion" to the ship's captain, Robert FitzRoy, who sought intellectual company as much as relief from solitude. The voyage itself was intended as a hydrographic survey, not a theoretical enterprise. Only retrospectively did Darwin's notebooks, filled with fossils, finches, and geological observations, cohere into what would later be called the theory of evolution.

Both episodes are now told as origin stories. Yet in their own moment, neither felt like a beginning. They were shaped by accident, personality, and circumstance, by what might be called narrative contingency. The interferometer's silence and Darwin's accidental berth are reminders that scientific knowledge often appears through situations that resist narrative polish.

And yet, once knowledge circulates, it almost inevitably does so in the shape of a story.

Why Science Inevitably Becomes Stories

Science does not arrive as a narrative. It arrives as measurements, fragments, disagreements, and failures. But to be communicated to peers, to the public, to posterity, it must be arranged. A sequence must be chosen. A trajectory implied.

Long before "narrative" became a term of art in the humanities, people relied on stories to make sense of everything. The literary theorist Walter Fisher described this tendency as narrative rationality: the idea that humans evaluate claims not only by logical consistency, but by whether they hang together as a story. Scientific facts do not exist outside this condition. They are understood through it.

It is here that a late-twentieth-century observation by Kurt Vonnegut became unexpectedly useful for me: In lectures and interviews, Vonnegut sketched simple graphs plotting time against a character's fortune. The shapes were crude: rises, falls, recoveries, but immediately legible. Stories, he suggested, have shapes.

Vonnegut did not intend this as a theory. But taken seriously, the idea reveals a constraint: once knowledge is narrated, it acquires a curve. Someone or something rises or falls. Fortune changes.

I have drawn, over time, on Kurt Vonnegut's suggestion to "sketch the shapes of stories" as a practical lens in my work with scientific narratives. Not as a formal method, and certainly not as a theory to be applied wholesale, but as a working tool, one among others, tested against the constraints and demands of real communication situations.

Approaching science stories this way gradually shifted my attention. The question stopped being only what these stories explain, and became whose fortune they implicitly trace. Across historical case studies and contemporary science communication, a recurring pattern emerged. Most narratives concentrate their emotional and narrative energy around one of four focal points: people, process, product and uncertainty.

These are not formal categories, nor are they proposed as a closed model. They function instead as convenient tools, ways of organizing attention, expectation, and consequence. I did not arrive at them by deduction, but by repeated exposure: the same narrative tensions resurfacing across different contexts, institutions, and audiences.

A System of Four Narrative Modes

Before examining each in turn, it is worth understanding how they relate to one another. These four types are not mutually exclusive; they are better thought of as different answers to fundamental questions about whose fortune is being tracked in a given story.

- People ask: Who does science?

- Process asks: How is science done?

- Product asks: What do we now know?

- Uncertainty asks: What remains to be decided, and what does it mean?

The most effective science stories often weave through all four, though one typically dominates. A biography may center on People, but strong pieces in this mode integrate Process and Product, showing not just “who” did science, but “how” and “what” they discovered. Similarly, a product-driven explainer that feels hollow usually lacks embedded People and Process contexts. The four types are thus less a taxonomy than a vocabulary for attending to which proportions of emphasis a story allocates.

Moreover, each type tends to align with certain shapes in Vonnegut's vocabulary of story arcs. People's stories often follow heroic ascent patterns or arcs of fall-and-redemption. Process stories typically trace zigzagging uncertainty before arriving at insight. Product stories move from ignorance to clarity. And Uncertainty stories: the rarest and most challenging, hold open the possibility that no single resolution awaits.

This layering is important: to understand science storytelling is to recognize not just the individual types, but how they combine, compete, and sometimes contradict one another.

The People: Heroism and Its Discontents

Here the narrative tracks the fortunes of individuals or communities who do science. These are stories not about scientific facts alone, but about people. This narrative mode is familiar in "people behind the science" series, anecdotes in research blogs, first-person testimony, and biographical profiles.This curve is powerful. It animates Archimedes, Darwin, Newton, Einstein. It is easy to remember, easy to teach and epitomise by the Nobel Prize. But it also demands simplification. The tendency has gone so far that collective labor collapses into individual genius.

People's stories focus on individuals: discoverers, geniuses, pioneers. They are the most familiar and the most seductive. Their narrative shape is typically heroic, an ascent from obscurity to recognition.

These stories are not false, but they are incomplete. Science is rarely the work of a single mind. It is collaborative, distributed, and embedded in institutions. Often the contributors to a groundbreaking discovery provided essential work far removed in time or space from the famous "genius." When people's stories dominate, they compress networks into names and labor into legend.

The consequences are well documented. Rosalind Franklin's central role in producing the X-ray diffraction images that enabled the DNA model was long minimized or erased. Her expertise was reframed as technical assistance. Credit followed narrative shape, not epistemic contribution.

This is not an accident. Feminist, philosophers of science, have shown how certain figures become narratively "legible" as scientists, while others do not. The heroic arc favors those already authorized by gender, race, class, and institutional position. Moreover, when non-dominant communities do appear in science stories, they are often cast as “subjects” of science, patients, study populations, beneficiaries, rather than as “agents” of scientific work.

That narrative shapes reflect power becomes clearest in the People mode. Reworking these narratives requires not just choosing different shapes, but attending to who has authority to narrate, and whose labor gets credited versus compressed into legend. Consider Alan Turing: his mathematical genius and cryptographic work are well documented. Yet for decades, his life was told in a shape that systematically excised his sexuality, as though his scientific identity could be cleanly separated from his personal one. When his sexuality finally enters the narrative, it often does so not as integral to his character, but as tragedy or scandal, an addition that disrupts the pure scientist frame. This is a narrative choice: science stories “can” weave personal and professional identity together, but institutions and conventions often resist that integration, creating a kind of narrative erasure where full humanity is sacrificed for institutional comfort.

Reworking people's stories does not mean abandoning narrative appeal. It means changing the shape: from solitary ascent to collective endeavor, from genius myth to epistemic accuracy. It means asking, persistently, “whose” story we are telling, and what labor and identity gets preserved in the telling.

The Process: “The Long Middle”

Process-centered narratives are common within scientific practice and teaching but rare in public retelling. 

Yet this shape is pedagogically rich. It teaches how knowledge is made rather than revealed. It preserves narrative contingency, the sense that things might have gone otherwise. The story of penicillin discovery in popular culture centers on the anecdotal moment of a forgotten dish and a lucky observation. Yet there is an entire story about lab processes, etiquettes, and operational methodology to be told and one that is told in scientific training, though rarely to broader audiences. The laboratory is not a stage for eureka moments; it is a “space of work”, and that work is iterative, methodical, and full of dead ends.

Stories of scientific process are, in their own way, the modern equivalent of Odysseus' wanderings. They dramatize uncertainty, dead ends, false starts, sudden breakthroughs, and the slow accretion of insight. The protagonist here is neither person nor idea, but the very methodological adventure of science itself. These narratives often resemble the “Which Way Is Up?” arc or the Creation Story that moves from chaos to order. They invite the audience not simply to know results, but to sense the rhythm and flow of inquiry itself. In recounting the twists and turns of research, where a failed experiment might be as instructive as a confirmed hypothesis, they reveal something rarely acknowledged in polished summaries: science is “becoming”, not just “being”.

In the Michelson and Morley story, had later discoveries not come along to retrofit the entire storyline and contextualize their work as part of a larger process, their contribution would have joined the millions of lab stories that never went beyond university walls. The reason is this: we are not very good at sending process stories outside of the university without being dramatized, given an Odysseus-like shape, for the consumption of non-professionals. They require what we might call narrative infrastructure: not just the facts of the work, but the meaning of the work, embedded in recognizable emotional and temporal patterns.

The Product: Endings That Consume Their Beginnings

When science communication puts the "product" first, the idea, the law, the discovery, it usually does so through explanation. The protagonist is no longer a person or a process, but an abstract result: a piece of knowledge moving from ignorance into clarity. These stories often follow a familiar arc: "We once thought X, now we know Y." They closely resemble a “Creation Story” shape in Vonnegut's vocabulary, where confusion gives way to order.

This is the most widespread form of science storytelling. It dominates educational material, popular science books, and explainer journalism, where clarity, simplicity, and forward progress are highly valued. It is the default mode of institutional communication and Science journalism, the most remarkable avatar is sensational science journalism.

As a result, many of these stories are told backward. They begin with the conclusion and compress everything that came before into a sense of inevitability. The ending is known in advance, and the path toward it appears smooth, logical, and uncontested. The problem arises when reality does not deliver the promised ending. When the expected conclusion fails to arrive, trust often collapses along with it. In contemporary science communication, especially news-driven communication, this risk is amplified. Research institutions and laboratories tend to communicate most intensely around results, because these moments are closely tied to visibility, legitimacy, and funding. Communication success is often measured through immediate indicators: clicks, impressions, engagement, headlines. What is frequently left aside, or postponed, is the question of how these narrative choices shape audience expectations. When a story is presented in a form that culturally promises a clear and satisfying ending, its failure does not register as uncertainty or complexity; it registers as disappointment or deception. This effect has been visible in public reactions to climate models, artificial intelligence, and biomedical research. The product curve, when applied to open-ended or uncertain science, can generate frustration rather than understanding.

The consequences are only visible later, when public perception feeds back toward scientists themselves, as happened starkly during the COVID-19 pandemic. When vaccine efficacy was communicated as settled fact, adjustments to recommendations felt like a contradiction. When pandemic timelines were stated with confidence they could not hold, later revisions registered as broken promises rather than updated understanding. The product narrative, told too cleanly, had set an expectation the science itself could not meet. This is not a failure of communication skill. It is a failure of narrative honesty.

The Uncertainty: Following What Resists Resolution

The rarest story shape in science communication does not focus on progress or arrival, but on limits. Its curve does not rise toward a conclusion; instead, it traces the edge of what cannot yet be known.

This shape usually appears in the margins: in footnotes. It is slow and resistant to spectacle. It offers no clear victory and no satisfying ending.

Some science stories have no single individual, method, or discovery at their center. Instead, they ask broader questions: “What are we becoming? What might be lost? What could still be redeemed? What do we owe to futures we will not see?” These are stories that touch on long-term consequences and shared responsibility. They are less about answers than about ongoing questioning.

Carl Sagan's “Cosmos” is a powerful example of this mode, though rarely recognized as such. Sagan did not simply explain stars or equations. He placed humanity within vast cosmic timescales, creating a narrative that was both humbling and energizing. He was tracing the fortune of “humanity itself” in relation to cosmic and scientific knowledge, asking what it means to be a small, fragile species on a small planet, armed with the power of understanding but also the capacity for self-destruction. Climate change, artificial intelligence, and pandemic preparedness invite the same narrative mode. They describe collective futures shaped not by a single breakthrough, but by choices we make or fail to make together.

In Vonnegut's vocabulary of story shapes, these narratives often resemble “Old Testament” arcs, where gifts are misused and consequences unfold, or “New Testament” arcs, where crisis opens the possibility of renewal. Consider contemporary climate communication: it often follows an “Old Testament → New Testament” hybrid. "We inherited industrial prosperity and scientific power, now we face the climate crisis, but science and policy transformation could still redirect our course." Similarly, artificial intelligence narratives frequently trace a “From Bad to Worse → New Testament” arc: "AI could amplify surveillance and inequality, accelerating existential risks, unless we act now to embed ethics and oversight."

The Long march of Narrative Choice

There is a temptation, particularly in moments of acceleration and fragmentation, to blame new formats for old failures. Short videos, social platforms, influencers, these are often cast as enemies of rigor. Yet this diagnosis confuses medium with method. Storytelling quality has never been bound to duration: parables were meant to illuminate in seconds.After all what differentiate modern forms of storytelling from one of the most pivotal moments for science communication that became Richard Feynman demonstration on Challenger issue?

What contemporary influencers demonstrate is not the decline of storytelling, but its continued potency. To generate curiosity, affect, and momentum in a brief span requires genuine narrative skill. The form is not trivial. What is often missing is not competence, but intention.

This returns us to a harder question: why were certain truths not told when time and space were abundant? Why did Rosalind Franklin's role remain marginal in textbooks unconstrained by brevity? Why did Alan Turing's scientific ascent coexist for decades with a narrative that systematically erased core aspects of his identity and the price he had to pay for being brilliant in his field while gay? These omissions cannot be blamed on format constraints. They reflect “choices” about which curves feel acceptable, which complexities are allowed to persist, and whose full humanity gets preserved in the story.

Legends spread easily because they follow familiar shapes. Evolution remains widely misunderstood not because it lacks drama, but because it resists intention, climax, and moral design. Its difficulty is not explanatory but “narrative”. 

Science communication in its most honest form must grapple with this. It requires what we might call narrative integrity: the willingness to preserve ambiguity rather than resolve it, to honor the labor of knowledge-making rather than erase it, to make room for voices and perspectives that do not fit the familiar heroic shapes.

 Conclusion: The Shape of Responsibility

We began with an interferometer that refused to say what its builders expected to hear. The Michelson–Morley experiment was a non-event that, over time, became a pivot point for physics. Yet this retroactive meaningfulness is precisely what troubles us. In the moment of its silence, the experiment was simply baffling and stories are rarely baffling. We tell stories to resolve confusion, to make meaning settle into place.

But science is not always ready to settle. Knowledge is distributed, incomplete, contested. It arrives unevenly across time and communities. And yet the pressure to narrate it to choose a shape, find a protagonist, arrange a curve is relentless. This pressure is not neutral. It favors certain stories over others, certain tellers over others, certain “kinds” of understanding over the uncertainty that often precedes it.

The four narrative modes sketched here:People, Process, Product, and Uncertainty, do not exhaust the ways science can be told. They are not a framework to be applied from above, but a vocabulary for recognizing what we are already doing when we choose to tell science stories at all. When we foreground individuals, we implicitly ask “Who counts?” When we trace a process, we ask “How is knowledge made?” When we deliver a product, we ask “What do we know now?” And when we sit with uncertainty, we ask “What remains to be decided, and what do we owe to futures we will not see?”

The Rosalind Franklin case is an ongoing reminder that narrative shape and epistemic justice are intertwined. When we tell heroic People stories, we risk compressing collaborative labor into individual genius. When we tell backward-told Product stories, we risk generating trust collapse when reality refuses the promised ending. When we rush past Process, we lose the pedagogical and epistemological richness of how knowledge actually becomes known. And when we suppress Uncertainty, we foreclose the possibility of collective deliberation about what science means and what we might do with it.

Science communication is not, finally, a technical problem of transmitting data or a rhetorical problem of persuading audiences. It is a cultural practice through which we negotiate the stories we tell about knowledge, shape what kinds of knowledge are possible, who gets to contribute to that knowledge, and what responsibilities we acknowledge once we know something.

Vonnegut's insight, that stories have shapes that can be graphed, was offered lightly, even humorously. But taken seriously, it reveals a constraint and a responsibility. Once we narrate science, we imply certain curves of fortune and certain endings. We foreground certain protagonists while others recede. We make implicit promises about where the story will go.

The practice of science communication, at its best, is recognizing that how we tell these stories matters as much as what we are telling.  Science communicators carry the responsibility of choosing whose fortune rises in the telling, and who falls away into the footnotes and the forgotten. Because in that choice lies something that matters: an act of epistemic justice, a preservation of what the making of knowledge really is, what kind of science culture we are building, together.