1.1 Introduction

Scholars of scientific life see it filled with experiments, models, theories, descriptions, observations, categories, etc. It is equally full of narratives. Yet the levels at which narratives work, and the kinds of things that scientists come to understand through the activities of developing their narratives, are not easily described in terms of any specific ambitions or functions. Narratives themselves may be understood as a broad class of ‘epistemic genre’, to use the label that Reference PomataPomata (2014) developed, essential to the representation of scientific knowledge.Footnote ¹ But narrative is more than just a means of representing such knowledge; rather, prior to such representations, narrative-making plays a wider role in the sciences as a means of sense-making. In contrast with Reference CrombieCrombie’s (1988) historically situated categorization of ways of doing science, an account developed further in Reference HackingHacking’s (1992) philosophical analysis, narrative-making is not mainly about how scientists investigate the world but rather about how they make sense out of those investigations. Narrative-making does not satisfy epistemic questions and worries in the way the interventionist and observational modes of doing science described by Hacking (and others) – such as experimenting, category making, statistical work and case-making – can do. Narrative-making and -using, by contrast, are more closely aligned with ontological questions, or, rather, scientists’ claims in their ‘narratives of nature’ are ontological claims about the way the world is and works. The role of narratives piggybacks onto the epistemology of those other, more interventionist modes of practising science. So, while narrative usage may overlap in places with Pomata’s notion of ‘epistemic genres’ and can be an accompaniment to Hacking’s modes of doing science – narrative-making and -using fulfil other distinct roles for scientists, roles that need separate recognition.

Narrative emerges from this volume as having three functions for scientists: narrative-making operates as a means of making sense of their puzzling phenomena; it provides a means of representing that scientific knowledge; and it provides resources for reasoning about those phenomena. These three functions are related: it is because scientists often make sense of their world by making narratives that they then use those narratives to represent what they believe they know, and thence to reason with them. I propose we think of narrative as a ‘technology of sense-making’ that enables scientists to bridge between their interventionist activities of exploring the world and their knowledge claims about the world, that is, between their epistemic and ontological realms. To label narrative a technology may seem rather strange, but we are in some interesting company here. The philosopher John Dewey argued that the notion of technology was not just about how to make things in the economy, but equally attributable to the abstract and intangible work of enquiry and deliberation involving cognitive work – just as we find for narrative in science.Footnote ² His contemporary, the sociologist-economist Thorstein Veblen, insisted on the priority of the human element in designing, making and using a technology. While narrative-making, -using, and -reasoning start with the scientist and their community, it is worth remarking that narrative also embeds its own technical elements and attributes. These three separate but related functions of narrative, broadly understood as a technology of sense-making for scientists, may be recognized in the chapters of this book by observing whether narrative is being used as a noun, verb or adjective.

All those nouns of scientific practice – experiments, models, theories, descriptions, observations, categories – hide actions and activities: experimenting, modelling, theorizing, describing, observing, categorizing. Other elements that scientists use don’t immediately convert between nouns and verbs – data has to be given its own multiple verbs (‘to gather, clean, assemble and prepare’), just as laws have ‘to be discovered or made’. Narrative is akin to laws and data: easily understood and effective as a noun, its scope as an activity is not quite so obvious; yet appreciating that scope is critical for understanding the broader role of narrative as a technology for scientists. The quintessential feature of narrative is that it shows how things relate together, so that constructing a narrative account in science involves figuring out how the elements of a phenomenon are related to each other. This is why narrative-making and -using are conceived here as a technology, one that enables scientists to make sense of their phenomena.

These basic usages of narrative in noun and verb forms are important, of course, but they might be still awkward, and limited, if we want to go one step further and conceive of narrative as flourishing in the knowledge-claiming activity of the sciences. In this respect, the adjectival form is more immediately useful: so, ‘narrative account’ and ‘narrative description’ might both be taken for granted. And, while ‘narrative inference’, ‘narrative argument’ and ‘narrative explanation’ might initially sound strange (even perhaps contradictory), it will turn out that we need these terms, for the narrative form does overlap in usage into these scientific activities of reasoning and knowledge-making. Thus, narrative as an adjective works as an attribute of a certain form of reasoning: giving a satisfactory narrative account may go beyond sense-making into the kinds of reasoning associated with inference and explanation.

None of these uses of the term narrative – in noun, verb or adjectival forms – should be problematic if we can find ways to appreciate the active work that narrative does in our sciences, particularly if we can figure out its features and its functions, just as we have for data and laws. These grammatical labels give clues, but only clues, to the ways in which scientists develop, create and use narratives in their various fields, for various purposes and in conjunction with various other forms of scientific representation and knowledge-making activities. These language terminologies need to be filled in with examples and hardened through analyses to reveal the active work we attribute to narrative in science, and so to appreciate how narrative operates as a technology for scientists in doing science.

There are, of course, many commentaries about narrative in other domains, especially in the fields of literature, narratology and legal studies. Narrative scholars from the domain of literature typically focus on the narrative as text: its plots, its structure, temporal and spatial organization, its eventfulness and cognitive function, as well as its rhetorical and aesthetic components, and terms of affect. Narratologists tend to focus on the narrators, readers, what constructions narratives follow, and their requirements for narrative tellability. It is fair to say that with few notable exceptions, neither group focuses especially on connections of narrative with knowledge-making.Footnote ³ So, in an important chapter, Kim Hajek explores what is narrative about ‘narrative science’, and thus extends the relevant intersections of those fields with our agenda (Chapter 2). Discussions in the field of law about narrative range over matters of rhetoric and affect, but have an equal interest in the putting together of evidence, and the role of ‘theory’ – meaning both the hypothesis about what happened in a particular case, but also the concepts from law that need to be taken into account.Footnote ⁴ As such, these latter interests fit closest to those of this chapter. But rather than work comparatively with this legal literature I treat narrative in science on its own terms – in order to examine how it makes itself ‘at home’ in the scientific knowledge environment.

Narrative is a broad, expansive term (with many definitions in narrative theory), and the challenge has been to develop an analysis which is insightful for scientists’ creation and use of narrative. Our research shows narrative to be an enabling, general-purpose technology, widely used by scientists within their own different communities to fulfil certain functions in their scientific work – even when they don’t use the word or recognize that label for their activity. It is important to note the limits of this claim: narratives are not found in all aspects of all sciences. Rather, they fulfil certain kinds of function with some regularity in some sciences, or some sites of science, and in conjunction with some methods of doing science. By tracing this (sometimes hidden) narrative activity, and its locations, we can understand both what is different and what is generic in these usages in different sites, and so develop an understanding of narrative in the domains of science.

1.2 Narratives of the Field

The first challenge we address in this book is to see and locate the narratives that appear in our sciences. The most obvious narratives found in science may be those wrap-up accounts in publications resulting from the activities of scientists. In modern science, these are usually impersonal narratives,Footnote ⁵ cut down to the essential actions that scientists tell of how they went about their research: their ‘research narratives’. Less recognizable, but still apparent, as Robert Meunier argues (Chapter 12), are their ‘narratives of nature’: the narratives – ‘as if told’ by natural, human and social life – that those scientists have tried to reveal, recover and make sensible. And, as he points out, scientists’ research narratives often twine in symbiosis around their narratives of nature.Footnote ⁶ This has fruitful consequences: the researcher–author, in guiding the scientist–reader along the path of their activities, enables the latter to gain practical familiarity with the former’s narratives of nature, particularly with any new elements and concept set in use.

A broader category of narratives can be found that seek to define and lay boundaries to new approaches for a whole field, or maybe to delineate a new interstitial field. These field-making narratives might be more or less reticent in their agenda. Grand ones are epitomized in the self-proclaimed narratives of those seeking to automate and computerize the whole of mathematics. Stephanie Dick (Chapter 15) discusses two such competing self-narratives in late twentieth-century American mathematics: one group sought to reformulate all mathematical knowledge into one single form, and the other to enable all mathematicians to contribute elements in their own format.Footnote ⁷ Their politics of control vs. pluralism were explicit. Other field narratives may be more opaque, evident only in their alignments and commitments, to be discovered by an outside reader, as Dominic Berry (Chapter 16) does in looking at how ‘synthetic biologists’ positioned themselves between engineering and biology in defining and growing their own field. He uses longue durée changes in history writing – from chronicles through genealogies to narratives – to argue his case. These are important categories. Chronicles report events solely based on their place in a time sequence without paying attention to any relationships between those events; genealogies focus on the ‘family’ (broadly construed) relationships between the events or objects; narratives provide an account of the relationships between events or objects (whether or not these relationships are tied together in a time sequence or by family connections). Among narratologists, there is a widespread view that a chronicle does not count as a proper narrative because the relational content is absent, while genealogies are just a subset form of narratives. Anne Teather (Chapter 6) adopts the same categories to show how new technologies of dating in archaeology have effectively changed narrative practices in that field. Whereas archaeologists used to tell genealogical accounts to frame the periods of prehistory (e.g., the Neolithic period), more recent technologies of investigation have created the more limited chronologies or chronicles.

Certainly, the narratives of nature – narratives of how the world is and how it works (whether it be the natural, human or social world) – are sometimes much harder to see than these research and field-making narratives. Narratives of nature are more likely to be found implicated with, or inside, other accounts of scientific activity. Like those sherds and trenches of Teather’s archaeological sites, these traces of narrative point to the scientific activities that created them, and from which we must reconstruct the power that narrative-making and narrative-using have in such spheres.

1.3 Narrative: A Means of Scientific Representation

The core function of what narrative does is to bring and bind elements in a subject field together. Narrative-making in the sciences can be found in theorizing, in creating an adequate description of empirical materials or in marrying them to each other in ways that embed ideas and concepts, that is, in activities of sense-making and knowledge-making (examined in sections 1.4 and 1.5). Since the narratives that result from these activities express, or make evident, these connections between elements in a scientific domain, narratives can be treated as a form of scientific representation akin to other forms of representation. What are the characteristic aspects of such representations, and the implications of this way of understanding the role of narratives in science?

First, narrative representations found in science may appear as free-standing or separate pieces of verbal text – in ordinary or natural language. They might be embedded in visual representations (drawn into schemas such as diagrams of mechanisms or detailed representations of empirical matters in graphs), or even expressed in the completely formal languages of abstraction and mathematics. Wise (Chapter 22) contrasts the possibilities of natural and formal languages, and the extent to which they do different kinds of work, and say different things, and thus why narratives in the two forms are not simple translations or transpositions of each other. Depending on the science in question, the narrative form of representation will be more or less formalized, more or less abstract, and may have more or less dimensionality of elements compared to other representational forms of diagrams, equations and so forth. But, whatever their form and language, it is typically the case that they are ‘community narratives’, to be understood without further explanation or accompanying text only by those in the expert community who use them. Mat Paskins (Chapter 13) translates/explains, for us lay-readers, the ‘chemese’ of chemical reaction diagrams depicting the synthesis of particular molecules. He points out that early twentieth-century versions told a different narrative from early twenty-first-century versions of essentially the same representation: in early years, the ‘equation’ expressed the sequence of steps taken to synthesize a certain chemical, but in later years, such diagrams came to narrate the chemical reactions that took place. The ‘cartoon’ narrative shown in Andrew Hopkins’s chapter (Chapter 4) relates what happens in a meteorite impact as material explodes, flows out and gradually builds up deposits on the ground. This requires, for the lay reader, a lengthy verbal narrative that lets us follow the combinations of interacting processes and outcomes from these geological events.Footnote ⁸ In other cases, indirect representations of nature (such as mathematical models) are manipulated to show the narratives implicit in visual schematic representations. We find such narratives in the computer visualizations from simulating snowflake growth and the processes of chemical reactions, as shown by Reference WiseWise (2017); the latter offers an alternative free-standing, time-stepped, visualization of the chemical reaction ‘equations’ found in Paskins’s paper (Chapter 13). Such narratives give clues to the density of knowledge that typically lies behind formal language representations.

Second, more often than free-standing independent forms, textual narratives are strongly co-dependent with other forms of scientific representation, such as charts, graphs, drawings, maps, matrices, models, formulae and so forth. Such textual narrative accompaniments might well be an essential part of the identity of those representations, whether of the evidential diagrams in graphs or of the theory-based representations found in models. The classic well-known example is Darwin’s pictorial ‘tree of life’, which – when read alongside textual information – offers a shorthand depiction showing how evolving species branch, or die out, or survive. It is a kind of genealogy – but a conceptual tree not a report of observations. Greg Priest describes this as a ‘scaffold’ on which we as readers can stand to ‘create narratives that enable us to understand’ Darwin’s account of natural evolution.Footnote ⁹ The infamous ‘prisoner’s dilemma’ model from economics (which was soon transferred to other social-science and biological domains) consists of a mathematical matrix, a set of inequality conditions on those numbers, and a narrative text of the possible behaviours of the ‘prisoners’ given the ‘dilemma’ of their situation (termed by economists, ‘the rules of the game’). The narrative is an essential element in identifying the game and differentiating it from others that may look similar, for the matrix and inequalities are both insufficient (see Reference Morgan, Creager, Norton Wise and LunbeckMorgan 2007). Combinations of text and drawings (keyed with numbers to each other) are found as essential partners in communicating narrative accounts of metamorphic changes in the insect world (from egg to caterpillar, larva to butterfly), as seen in Mary Reference TerrallTerrall’s (2017) discussion of eighteenth-century accounts of this phenomenon. Such matching media of visual and text narratives, in which neither is primary but each depends on the other, are also used to explore possibilities of hypothetical events as we see, for example, in D’Onofrio’s account of eighteenth-century generals re-running historical battles according to geometrical lines (in Anthology II).

There is often a kind of bonding here, rather than co-dependency, of forms and functions. Narratives embedded in formal languages and visual representations often provide a highly efficient rendering of the materials of events. The phylogenetic trees of the evolution of the kangaroo and other marsupials discussed by Nina Kranke (Chapter 10) express a travel saga that charts their geographical and biological evolution over time and space as the species evolved while members of its ancestral population ‘journeyed’ from South America to Australia. As she shows us, such ‘trees’ exist in multiple formats – showing in succinct ways, but with distinctly different variants, the narratives of different kinds of family trees or genealogies. Some of these are for professional audiences, some for museums; some are plain, some ‘filigreed’; some read upwards, some downwards, some sideways. There is no one convention despite the related kinds of narratives that are told by these related kinds of trees. There is surely a family tree of such trees, a genealogy of trees, going forward in evolutionary biology from Darwin’s tree of life, and going back in time in a long tradition of drawing human dynastic trees.

This complementarity, and bonding, of narratives alongside and inside alternative representations show how narratives fulfil their representing functions in the sciences and how narratives do the kind of representing work they do. These kinds of co-dependency also suggest there are no strong reasons to privilege narratives as a text form when narratives can find their primary expression in other forms of representation. Narratives in the visual, schematic or even mathematical forms of representation may perform by showing as much as by telling; they are designed to be ‘seen’ by others in the same community of scientists who know how to ‘read’ them. For example, Martina Reference 30Merz, Howlett and MorganMerz (2011) recounts how readers of a scientific paper in a particular field of physics will automatically follow the diagrams that are arranged in a clockwise fashion at the beginning of the paper – these ‘show not tell’ the research narrative of the salient activities, and readers follow that visual narrative before bothering to read the text of the paper. In some cases, nature’s entities show their own narratives directly. Devin Griffiths (Chapter 7) tells how the Darwins set up plants so that their roots traced out their own growth narratives in scientific experiments. Starting from these visual autobiographies, Darwin constructed narratives at three different genre (i.e., generic) levels: ‘micro-narratives’ of individual plant life, the ‘novella’ of the life history of plants and the saga of biological evolution.

In sum, I argue two points: first, that narratives (like models, diagrams, equations, graphs, etc.) can be understood as a mode of representing scientific things (ideas, theories, processes, evidential records, relations, etc.); and second, that such narrative forms are quite likely to hybridize or be co-dependent with, or even entirely embedded within, those other media of scientific representation.

1.4 Narrativizing: A Means of Sense-Making

Narratives in science are not given by God, or by some other external authority, but designed and made by scientists in their research communities. Attention has to be given to the ways that they create narratives as a means of sense-making – to the active work of narrative formation in the practices of scientists, especially with respect to their narratives of nature.

There are two points here:

1. 1. I take it that the quintessential function of narratives of nature in science lies in making, or unravelling and remaking, connections between things. The world presents many puzzles and scientists seeking to understand their phenomena in their ‘narratives of nature’ have to figure out how that part of their world works, and to give an account of how the bits of it fit together that makes sense. And, like other ways of making other kinds of scientific representation (such as models, schemas, diagrams, tables and category descriptions), narratives have to be developed, tried out, calibrated against other information, reconfigured and re-thought-out to fit the materials that need to be understood. I have in mind something like ‘narrativizing’ – which has the primary and distinctive aim of ‘bringing and binding’ together the heterogeneous elements associated with the phenomena in a field.

2. 2. Following this, I ask: what relational ‘grids’ and scaffolds do scientists use to build their narratives? This is not a question about the structure of the final narrative (whether it has to have a beginning, middle and end with a change of state (see Reference Carrier, Mertens and ReinhardtCarrier, Mertens and Reinhardt 2021), nor whether it is primarily ‘tellable’ in terms of sufficiently interesting events (see Reference RyanRyan 1986), nor on its ‘affect’ and how it facilities multiple connections (see Jajdelska, Chapter 18). Rather – this is a question about the basic dimensions of relations that scientists use in building or creating or supporting their narratives; it is about the lines of relationship on which narrativizing goes on.

First: what happens in narrativizing? The basic role of narrative and its special function for scientists is to put diverse materials into relation with each other through time, or across space, or through other conceptual dimensions (such as classes in society, or elements in an ecology) in order to form a coherent account of a phenomenon. Narrativizing is a way for scientists to organize their bits of scientific knowledge to create sense out of their relations. Narrativizing serves to join things up, glue them together, express them in conjunction, triangulate, splice/integrate them together (and so forth). Yet, the need to clarify relations between things means that narrativizing sometimes means scientists have to sort things out so that their interrelations can be seen more clearly.

One term that captures the challenge that scientists face when they make narratives – explicitly or implicitly – to help them order and relate the separate elements of their scientific knowledge into coherent accounts is configuring. This term comes from Reference MinkMink (1970 and Reference Mink, Canary and Kozicki1978), writing about the philosophy of history, but he remained opaque about the processes involved. Two other terms, discussed in Reference MorganMorgan (2017), offer recipes with more content for science narrativizing. Colligating comes from William Whewell, who used it to refer to the process of fitting together, under an idea, items primarily from the empirical domains of science (see Reference Cristalli, Herring, Jones, Kiprijanov and SellarsCristalli 2019; Reference KuukkanenKuukkanen 2015; and Reference Swedberg, Leiulfsrud and SohlbergSwedberg 2018). Juxtaposing was the other term I used then – to refer to the activity of pulling together separate elements known about a phenomenon, but that did not initially make sense together. Narrativizing, constructing a narrative, was a way to make sense of them and resolve initial puzzlement. (This followed a lead from Paul Reference RothRoth (1989), again for philosophy of history, rather than for science.) Both recipes offer the possibility for creating wider narrative-based understanding or even explanations (as we will see in section 1.5). I want to press the use of Whewell’s terminology of colligation for two reasons. First as a process (in verb form), colligating involves bringing elements together and binding them together just as narrative-making does; the outcome (its noun form) is equally appealing, for a narrative can be understood as a colligation. (A little care is needed here: while narrative-making in science can be understood as a process of colligating (the verb), not all colligations (nouns) necessarily come from narrative-making; for example, the elements brought together could be similar things, bound together in creating a category.)Footnote ¹⁰ Second, with these two insights of bringing and binding, it is easy to see how the process of colligation can cover the many varied ways in which scientists use narrative to bring together all sorts of different kinds of elements: empirical elements, theoretical arguments and speculative claims. These practices of colligation vary from site to site, and from science to science. Thus configuring elements into a narrative that explores a time-based, path-dependent system in nineteenth-century biology mobilizes a different mode of ordering and relating, both from the juxtaposing narratives of mid-twentieth century case studies in sociology and from the ‘how possibly’ puzzle narratives of modern mathematical and computer-based simulation.

These examples take us to the second point: how does this narrativizing go on? We find two main sense-making strategies, two main relational ‘grids’ for colligating: one based on taking a possible network of relationships as the main device for ordering materials, the other by ordering elements along space or time lines. ‘Grids’ are not to be understood as rigid measuring rods, but rather as a shorthand way to express the main domain upon which the process of colligation – the ordering and relating, the bringing and binding together of elements – happen. These different kinds of grid are not straightforward in use, and often they are used conjointly, because the materials that need to be knitted together in science narratives are not going to be simple connections between elements as if lined up along an individual piece of string, whether that string is a time or space string or a causal path string.

A ‘cat’s cradle’ offers an analogy for narrative-making for the first, causal/associational, version (a term offered in Anne Teather’s chapter). It is a net made from one joined-up piece of string that can be fashioned into several different network patterns. Each network pattern will be different, for it uses the same elements of the string arranged in different ways. Each network pattern can be understood as depicting a set of relationships; the nodes and spokes of the elements may denote an ambiguous relationship, or be causal in a mechanistic kind of way, or they may indicate a much looser association. Indeed, the benefit of colligating or narrativizing on a network grid is that the resulting narrative can be opaque about the exact nature of those relations; it can allow knowledge to be uncertain; it can allow for multiple perspectives; it can enable complexity to be maintained; and it can embrace context where the cut between content and context is unclear.

Time-line and spatial relations seem to offer simpler grids for narrativizing. But, in practice, scientists don’t rest content with creating narratives just by moving along a chronological time-line or arranging items across a spatial grid. Their use of time is not straightforward: they might use relative or absolute time; will cut time up into different units; work backwards and forwards over time, etc. And while time-based accounts in sciences may find narrative necessary, it is important to remember that time-based relations are neither a necessity for narrative, nor sufficient in themselves.Footnote ¹¹ Of course, things happen in time, and across space, but these may not be the domains in which relationships matter. And even where either time or space may be understood as the dominant dimension for observing change (as in fields such as geology, palaeontology, evolutionary biology and parts of anthropology, sociology and social science history), there is rarely any simple time or space sequencing of events. And often, these two major kinds of grids – relational and spatio-temporal – will mix together in the narrative and will interact. Sometimes, the time–space line enables the scientist to infer subject-matter connections, at other times the subject-matter connections enable the scientist to infer the time or space relations.

It perhaps helps to draw some comparisons. The main feature of the narrative form – that it fits elements together and reveals the connections between them – contrasts with other forms and modes of making and expressing scientific knowledge. The comparison here is particularly with those activities that list or rank elements of knowledge, those focused on activities of separating out similarities and differences between things, and the consequent listing, labelling and describing of such taxa and types. A list of fossil remains, or the table of chemical elements, or the species of natural history, organize or ‘order’ our knowledge according to weights, or categories.Footnote ¹² They produce nuggets of knowledge, orderings of knowledge, families of like and dislike things, and whole classification systems.

So, on the one hand, the configuring and colligating of narrative-making sit in contrast to the making of tables and categories: the former stitching together relations between things, the latter separating out different kinds of things according to their particular characteristics. On the other hand, those alternative forms of ordering and expressing scientific knowledge are also, like narrative, more than description, for they too are a means of organizing and representing our knowledge. Both narrative-making and category-making develop our scientific knowledge and facilitate our expression of our knowledge about the world rather than being primarily technologies of intervention in the world. And, as usual, there is a caveat: the sense-making quality of narratives (the attempt to find narratives of nature) can also work co-dependently with those other contrasting activities and forms in science (category-making, case-making, statistical thinking and so forth). Narrative ordering and relating do not always substitute, or replace, but may complement other modes of developing knowledge in science. Narrative-making is one potential element, often an essential one, in a multifaceted network of practices that enables scientists to develop ideas and accounts of their domains.

1.5 Narrative Reasoning and Knowledge-Making

So far, we have examined the ways in which narrative provides a means, an enabling technology, for scientists to make sense of their investigations, rather than being a means of those investigations. Yet, we have also seen that narrative-making is not a passive part of science, nor an add on at the end of work, but rather (as noted by Meunier) that scientists’ research narratives are symbiotic with their narratives of nature. Our cases in this volume suggest a more ambitious claim, namely that such narrative-making and -using activate scientific understanding and explanation. Narratives appear in chains and forms of reasoning associated with direct knowledge claims, which can best be expressed in terms of ‘narrative argument’, ‘narrative explanation’ and ‘narrative inference’. Once again, we see that these narrative usages do not provide a competitive path to other modes of scientific reasoning and knowledge claims, but a complementary one.

1.6 Conclusion

Narratives are made by people, perhaps mainly for enjoyment, perhaps for enlightenment, but also in the sciences for far more utilitarian purposes; thus my labelling them an enabling, sense-making, technology for scientists. I propose we go further than this, and think of narrative as a ‘general-purpose technology’ (GPT). This term comes from economists and economic historians who have focused on the use of a technology and its histories (rather than its invention or how it is reproduced), and on two particular attributes of such technologies, both of interest for this account of narrative as a general-purpose technology for science.Footnote ²⁴ First, GPTs are, as the term suggests, technologies with usage that is both generic in its main purpose, but gradually expands across a range of unexpected sites, fulfilling that main function in different ways, and becoming co-dependent with other technologies in the process. Steam power, electricity and computing all offer supreme examples of such GPTs: each has a general-purpose use but is harnessed in different ways for different specific purposes, just as narrative is harnessed across the sciences. Second, and less obviously, those scholars have noted the important role of users, and user-innovation, in the spread and development of those technologies into those multiple sites, and charted how those innovations created changes in economic and social life. For scientific life, our chapters have analysed the multiple and varied usages of narrative and shown how its general purpose of sense-making can be traced into narrative representation, reasoning and knowledge claims.

Of course, narrative is not a new technology, nor invented by scientists just for their use! It would be equally unhelpful to argue that narrative was introduced into science in a particular era, and that it became a revolutionizing GPT as it spread through the sciences in the way that steam power, electricity or the computer did for our everyday lives. Not at all. I am not claiming, nor did our project suppose, that narrative was introduced into science in the way that historians of science have argued ‘the experimental method’ was. Arguably, we could treat that ‘method’ as another possible GPT: historians have tracked how it came into the sciences in the early modern period, taking over the means of investigation and mantle of experiential knowledge, and gradually morphed into the method of controlled laboratory experimentation on the one hand, and field experiments on the other. It has now appeared under many guises (in computer simulations, in medical randomized trials, in thought experiments with models, etc.) and has grown into conjunction with other modes of investigation such as statistical methods and modelling – two other modes of doing science we might also label GPTs – to create the kinds of hybrid modes that characterize modern scientific practices.

In contrast to the laboratory experiment, narrative was surely always in science, and narrative-making and -using in science is a human activity, and so could easily become a social habit in new environments. Thus it surely has a history. Neither this chapter (nor our book) offers any serious history of the place of narrative in the sciences, although we can see a number of points salient for investigating that history of the changing roles, sites and manifestations of narrative.Footnote ²⁵ And we can suggest the kinds of materials that would be involved. For example, Reference Dear and DearDear (1991) points to the use of narratives of individual experience in reports of actual and thought experiments in the English tradition of the seventeenth century. Reference Holmes and DearHolmes (1991), in response, compares that tradition with French scholars’ narrative modes, which aggregated several experiments at once and which melded their experimental accounts with arguments about the nature of the materials. This is the kind of historical point when, for a particular site of science, narrative turns from being an epistemic genre (using Pomata’s terminology) into a technology that goes beyond simple reporting into something like narrative inference (while still relying on particular modes of intervention and reasoning, to use Hacking’s and Crombie’s ideas). Another hinge point in this historical account of narrative in science might be the one noted by Reference TerrallTerrall (2017) in the eighteenth century, when natural historians turned from pictures, narrative texts, or one plus the other, to keying the text to the pictures. Perhaps this is one of the moments when narrative became diagrammatic? These brief remarks suggest that whereas narratives in science may have been found largely as textual free-standing accounts in earlier centuries, the production and usage of narratives appear to have become increasingly intertwined with, and adopted into, other modes of doing science and making scientific knowledge over the last two centuries. In doing so, narratives and narrative-making may have changed in form, but perhaps not changed in their fundamental knowledge-making functions.

Those three GPTs of economic life – steam, electricity and computing – are called so not just because of their flexibility in use, but because they have infiltrated the ways we humans do things in ways which add power to, and expand, our human resources. Narrative, and narrative-making, have expanded or enlivened our human abilities and intelligence as scientists – just as different modes of doing science and different epistemic genres of scientific representation have done. For narrative – as we have suggested – the general purpose that makes narrative as a technology so useful to scientists in doing science lies in narrative’s sense-making possibilities: the power of narrative is to colligate elements together under conceptual frames to make sense of the phenomena that exist in the world.

2.1 Introduction: Narrative and the Narrative Science Approach

What do we mean by ‘narrative’ in enquiry into narrative science? How does the Narrative Science (NS) Approach relate to other scholarly interest in narrative? In everyday English, we most often encounter ‘narrative’ used to refer to an overarching position, or set of positions, on some issue – for example, there are competing ‘narratives’ of climate change,Footnote ¹ while marketers for a brand develop its ‘narrative’ to appeal to particular consumers (see, e.g., Reference SalmonSalmon 2008). More basically, ‘narrative’ serves as a synonym for ‘story’. The two gather literature into their associative constellation, such that it could seem straightforward in 2010 for Laura Otis to claim a ‘close affinity’ between literary studies and work in the history (less so philosophy) of science, due to a ‘common focus on narrative’ (Reference OtisOtis 2010: 570). With the overlapping ‘linguistic’ and ‘narrative’ turns, historians have read scientific documents ‘like novels’ (Reference CarroyCarroy 1991: 22),Footnote ² and sometimes joined literary scholars in tracing patterns of influence, shared elements or dissonances between scientific and fictional texts. These approaches have been enormously fruitful, but they disperse their analytic gaze over a wide and highly varied field of view. On the one hand, most studies in literature and science have tended to concentrate their attention on one or the other kind of text – usually novels, since most work in this domain is undertaken by literature scholars.Footnote ³ Much rarer are investigations which take full advantage of the potential for careful, detailed exploration of formal reciprocities and intersections between narrative fiction and scientific writing (Reference VilaVila 1998 and Reference GriffithsGriffiths 2016 are two examples).Footnote ⁴ On the other hand, when it comes to scientific texts, ‘narrative’ stands in too often for what is primarily an attention to language or metaphor, as in Reference OtisOtis’s 2010 reflections. When narrative appears in such broad terms, it loses its value as a distinct category of analysis. This chapter aims precisely to recover narrative as a discrete analytical category – of significance in its own right, and also as one mode of writing and thinking to be investigated alongside metaphor, themes, argument, genre, etc. in scientific texts and their literary counterparts. In promoting this ‘Narrative Science Approach’, I construe narrative in the specific technical terms of narratology.

Narrowing our perspective in this way has value, first, for understanding the histories and philosophies of science (HPS). As Kent Reference PuckettPuckett (2016: 8) puts it, ‘looking at and naming different aspects of [narrative] gives us the ability to see what is weird about almost any narrative’. Narratology (or narrative theory)Footnote ⁵ provides technical concepts and well-determined labels with which to discuss aspects of narrative; this chapter elucidates some fundamental narratological ideas for HPS scholars (my first set of readers) and demonstrates how these concepts help open up a peculiar set of features of scientific activity – ones we call ‘narrative’. Scientific texts are my priority, as they are in this volume and the wider NS Project; novels make few appearances in these pages. The formalized, technical framework of narrative theory lets us defamiliarize aspects of standard scientific texts like experimental research articles, but also to study how diagrams or computer-simulation movies function in story-like ways – I encompass all of these scientific outputs under the term ‘text’.Footnote ⁶ With tools from narratology, we can also point to imaginative processes undergirding certain forms of scientific reasoning. My analysis draws together the narratological work done in this volume and unpacks its workings, with the aim of promoting further use of rigorous narrative theory by scholars in HPS.

Such a NS Approach, secondly, has benefits for narratology more broadly, as well as for interdisciplinary research into literature and science. I thus also address this chapter to scholars in literary and narrative studies. (Indeed, bringing together a dual readership follows readily from my own interdisciplinary interests, and accords with the multidisciplinarity of the NS Project.) My analysis offers these readers an exploration of particular ways that narrative analysis plays out in historically and scientifically detailed enquiry. The contextual and technical expertise of historians and philosophers leads to perhaps surprising insights, which can, in a reciprocal movement, feed back into the work of narrative scholars. Studies of the kind in this volume provide much-needed, fine-grained analyses of non-fiction narratives in their particular historical and disciplinary contexts, for instance.Footnote ⁷ They also open up arenas for productive comparison of scientific and literary texts in strict formal terms. My argument, then, brings narratological endeavours – including the growing field of factual narrative – and HPS studies into dialogue, for the benefit of both areas of scholarship.Footnote ⁸

What the chapter is not, is a comprehensive introduction to narratological concepts – there exist many handbooks and critical introductions for that purpose.Footnote ⁹ Nor do I survey all the ways narratology could inform HPS scholarship. Rather, following Reference WiseMorgan and Wise (2017), I concentrate on how scientists use narrative when doing science – as opposed to when they popularize it, or formulate an argument for a wider audience – and what narratological concepts enable us to see and say about such uses. Analyses from the NS Project serve as my principal examples; indeed, even where narratological concepts do not appear explicitly, they wind through many chapters in this volume, providing more or less implicit support to contributors’ arguments. My purpose here is thus twofold. In serving as an introduction to this volume, this chapter sets out how the NS Project thinks about narrative qua narrative. One might say the chapter ‘translates’ commonalities in contributors’ approaches into (some of) the terms of narrative theory. But, like all translations, mine is not neutral; this is my analysis of how narratological concepts provide an angle of entry into this collection. At the same time, the chapter stands on its own as a proposal for what narratology and HPS have to offer each other as fields of enquiry, and where that kind of dialogue might lead. My argument both complements and sits as counterpoint to Mary Morgan’s introduction (Chapter 1) – quite deliberately; each of us offers ways of looking at this collection of essays and at wider scholarly themes that intersect them. We just do not take quite the same angle of vision. Commentaries by Sharon Crasnow and Norton Wise do similar kinds of work at the mid- and end-points of this volume (Chapters 11 and 22).

Use of narrative spans the sciences – mathematical, natural, human and social – as Morgan outlines in detail in Chapter 1. For the purposes of this introduction, I identify two major classes of narrative knowing, each of which is particularly susceptible to investigation using a particular kind of narratological tool. In the first place, there is the ‘mise en mots scientifique’ (after Reference AcquierAcquier 2010), or the ‘mise en récit’ (putting into narrative): the (re)presentation of scientific activities or findings in textual form, be that written, visual or spoken. Such texts, as material expressions of scientific work, are at once a product of scientific activity (think of a research article) and an index to the active process of narrative-making. Seen as output, the substantive ‘mise en récit’ takes nominal (noun) form – as a narrative – and overlaps with what Morgan calls ‘narrative representations’. Activity, by contrast, is verbal; what I see as the active flip side of the same ‘mise en récit’ is Morgan’s ‘narrativizing’. But, where Morgan treats the two as separate but related functions of narrative in science, I argue that they are thoroughly, even necessarily, interdependent when seen through the lens of narrative theory. Noun and verb, narrative-as-made and narrative-making, are two sides of the same coin. Both lend themselves to analysis through the output form, the text. Concepts from classical narratology serve to unravel this doubled nature of scientific narratives, as well as to pull out ways in which the events/phenomena to be recounted might differ from the way they are represented – which plots are told, from whose perspective, whether there are flashbacks. Such questions ultimately relate back to the fundamental distinction in narrative theory between story and discourse; this distinction, and what it reveals about scientific activity, is the subject of section 2.3 of this chapter.

Before undertaking this work of unpacking, however, it is worth asking where scientific narratives – as output, noun, representation – sit in relation to the kinds of texts usually studied by narrative scholars. This question is the subject of section 2.2. Until recent interest in ‘factual narratology’ (see Reference Fludernik, Fludernik and RyanFludernik and Ryan 2020), and even now, narratological categories have predominantly been applied to literary texts, which are readily accepted as being narrative in nature. The NS Approach, by contrast, does not formulate an a priori definition of what counts as a scientific narrative before asking whether we can productively employ narratological tools to unpack (some of) its functions.Footnote ¹⁰ Rather, contributors to the NS Project have examined both scientific narratives in the uncontroversial sense (like medical anecdotes or psychological case histories), and also (and more frequently) portions or characteristics of texts that might more readily be called ‘reports’, ‘accounts’ or just ‘articles’.Footnote ¹¹ (Indeed, the French term I have been using, ‘récit’, encompasses both forms.) The broad features of scientific narratives that I develop in section 2.2, using Reference Ryan and HermanRyan’s (2007) elements of narrativity, thus emerge a posteriori from the NS Approach.

This definitionally flexible approach becomes especially evident in my second class of narrative knowing in science. Similar to Morgan’s notion of ‘narrative reasoning’ (Chapter 1), I construe this form of knowing as something that a scientist does with a scientific text. Each of us places the emphasis on a different word in the pair, however. Reasoning is privileged by Morgan under her functional approach as something scientists do with and within narrative representations – a deliberate cognitive process, distinct from imagining or affective reactions. By contrast, I understand ‘narrative reasoning’ as cognitively broader, involving imagination, affect and reason, in variable combinations. What matters for me is the combined result of these cognitive processes: story-like representations constructed in the mind/imagination of scientist–readers as they undertake some scientific activity (reading mathematical proofs, interpreting diagrams, framing their field).Footnote ¹² The attention here is on the reader’s reception of a scientific document, and how it might share cognitive features with the reading of (literary) narratives, without presuming that the document is itself a narrative (representation). Ideas from cognitive, or post-classical, narratology are notably helpful for examining reader responses; I discuss these in section 2.4.

Importantly, this interest in narrative modes of reasoning does not mean the NS Approach makes any broad claims about narrative as a mode of human cognition; even less do we claim epistemic priority for narrative knowing. For all our definitional flexibility, we therefore set aside the perspectives of thinkers like Paul Ricœur (e.g., Reference RicœurRicœur 1980) or Jerome Bruner, for whom narrative fundamentally structures one or more functions of human thought (see Reference Crossley, Herman, Jahn and RyanCrossley 2010). Asking how narrative modes might enter into human cognition in general is a valuable question; it is just not one that we find particularly helpful in the context of this project. As David Herman presciently remarked in a Reference Herman1998 commentary, claiming primacy for narrative is to set up an ‘idyll of narrative’ (Reference Herman1998: 385), which essentially only reverses the epistemic hierarchy present in earlier philosophers’ ‘myth of science as univocal rationality’ (Reference HermanHerman 1998: 384).Footnote ¹³ Either hierarchization precludes fine-grained attention to the contextual nuances of science and narrative studies as historically evolving activities.

It is the evolution and intricacies of scientific activity which concern us in this volume; concomitantly, we do not take account of the historicity of narrative theory as a field of study. Rather, we make flexible use of a range of concepts from narratology and use them to interrogate the doing of science in its active sense: what in science is about narrating, constructing narratives, reading narratives? The narratological tools we employ, the places we find narrative, thus expand and contract with the contingencies of our case studies, and tend to draw from varied perspectives within narratology as a field of enquiry.Footnote ¹⁴ I reflect in my concluding remarks on what it might mean to look for narrative knowing in a historicized science of narratology.

2.2 Narrativity of Scientific Narratives

When asked, ‘what is a narrative?’, common usage, like some cognitive-science perspectives (Reference Crossley, Herman, Jahn and RyanCrossley 2010), holds that humans are innately able to recognize story-like configurations. Morgan, in Chapter 1, circumscribes the domain of scientific narrative along functional lines – what it does for scientists alongside or in place of tables, models, diagrams and so on. For their part, narrative scholars have long striven to develop a precise and logically coherent definition of narrative.Footnote ¹⁵ But NS contributors rarely begin with these kind of definitions, or even ask explicitly, ‘is it a narrative?’, about the documents or actions they propose to analyse.Footnote ¹⁶ Rather, as illustrated in this volume, contributors find it more immediately significant to plunge into examining a given document’s (or action’s) narrative characteristics and how those function.Footnote ¹⁷ This notably allows attention to the fragmentary or lumpy ways that narratives can appear in scientific work, which might be overlooked under too stringent an initial categorization.Footnote ¹⁸ Andrew Hopkins (Chapter 4), for instance, identifies sentence-level narrative chunks in geological research articles. These highly condensed narratives recount the transformations undergone by a rock formation, but are chiefly only recognizable as narrative by trained geologists. The narrative lies between the textual lines of the document,Footnote ¹⁹ so to speak, a point which emerges secondarily from Hopkins’s study.

In this section, I explore several characteristics of scientific narratives that can be identified through NS enquiry, taking narratologists’ definitional frameworks and theories as a sensible starting-point. Such comparison is additionally essential to developing a genuine dialogue between narrative theory and science studies. My preference is for Marie-Laure Reference Ryan and HermanRyan’s (2007: esp. 28–31) manner of classifying narratives according to a ‘fuzzy set’ of conditions on their narrativity.Footnote ²⁰ Ryan lucidly divides the degree of narrativity of a given text into a number of ‘dimensions’ and ‘conditions’ that span narratologists’ instincts and preoccupations regarding what narrative is. By using her scheme, we evaluate the degree of narrativity shown by a given document, not whether it should be ruled out (or in) as a narrative. Here, I work with three of Ryan’s conditions in order to interrogate some salient features of scientific narratives: whether characters in a story are individuals with a ‘mental life’; the importance of the ‘temporal dimension’; and the issue of narrative ‘closure’.Footnote ²¹ My discussion, drawing iteratively on chapters in this volume, opens up a few intriguing narratological features of scientific narratives – which may, in turn, inform further categorization work on narrative.

2.3 Formal Matters

2.4 Narrative Reasoning

For now, I turn to existing narratological understandings of reading practice and how they can illuminate scientific reasoning. No telling is without its implied or actual readers, and they too perform important work in narrative-making, in an interplay with the narrative as textual or visual material. In a sense, therefore, I move now from considering narrative as the dynamic relation between story and discourse, to considering an interconnecting relation between discourse/narration and reader. It is a move which brings us into the domain of cognitive narratology – a field that combines findings from psychology and artificial intelligence to explore relations between story-text and -language, on the one hand, and human memory, perception and affect, on the other.Footnote ⁵⁵ Concepts from cognitive narratology are well suited to tracing the kinds of processes occurring in a reader’s mind (or imagination) as they read a scientific text or diagram; notably, narratological concepts point us towards elements of scientific reading practices that might well be compared to ways people read fictional texts.

I construe such cognitive processes under the banner of ‘narrative reasoning’: they comprise story-like imaginative constructions which scientific readers generate when reading a research article or examining visual evidence.Footnote ⁵⁶ If the scientific text in question has a clear narrative discursive form, narrative reasoning in the mind may not differ greatly from the logic of the narrative on the page, or it might be inferred using more classical narratological tools (of the kind discussed in the previous section).Footnote ⁵⁷ Narrative reasoning is more distinctive as a component in scientific activity when story-like imaginative work is prompted by apparently non-narrative scientific texts – texts with very low narrativity (to link back to my earlier discussion). An example I have already evoked is the ‘implicit’ or ‘covert’ narratives of historical sciences like geology, which Hopkins argues only unfold as narratives to an informed reader. To interrogate narrative reasoning under my NS Approach is to examine the processes by which a scientist imaginatively replays such narratives, and, importantly, how these processes map onto particular textual elements. This explicitly adds a textual dimension to the narrative thought processes opened up by Morgan (Chapter 1). We might refer to tacit knowledge, scientists’ trained judgement, or their horizon of expectations – to invoke some concepts current in HPS and narrative studies. However important, these are not enough for rigorous narrative enquiry, since they operate on a more general level: they relate texts as a whole to broad-scale expectations or knowledge in a field. With the NS Approach, we can delve into the specifics of which particular elements in a research paper or diagram activate story-like imaginative responses, as opposed to other cognitive functions. Notions like narrative performativity and scripts allow contributors to this volume to begin this work.Footnote ⁵⁸ I briefly outline their findings in what follows.

As Elspeth Jajdelska emphasizes in Chapter 18, the question of who narrates a story and in what circumstances matters for its reception. Jajdelska transfers the notion of narrative performativity from the spoken to the written domain and, in a recursive move, elucidates its workings in a research article about cognitive science. Performative language is what early narratologists might have called properly literary language, in that it draws attention precisely to its aesthetic qualities. It thus bears a greater affective force and implicitly cues a certain imaginative worldview. The worldview thus rendered can encode assumptions or perspectives which support a researcher’s explicit argumentative position, as in the article analysed by Jajdelska. Importantly, under this framework, particular textual passages, or even a few words, can be identified as corresponding to a story-like cognitive effect – one which plays a highly significant role in the knowledge claims of this scientific article.

A different kind of small-scale textual (or visual) element that produces story-like reading is the script (Reference HermanHerman 1997). In her chapter examining how mathematicians read proofs, Line Andersen deploys this concept from early cognitive narratology to argue that mathematicians read proofs similarly to how people read fictional narratives. That is, portions of the proof call up a sequence of events or actions that are expected or appropriate in the context in question. These proof-segments operate, in other words, like the scripts in literary texts for events such as ‘eating in a restaurant, riding a bus, watching and playing a football game, participating in a birthday party, and so on’. As the AI researchers who developed the notion go on to say, ‘These scripts are responsible for filling in the obvious information that has been left out of a story. Of course, it is obvious only to those understanders who actually know and can use the script’ (Reference Schank and AbelsonSchank and Abelson 1977: 41).Footnote ⁵⁹ Andersen develops the correspondences between script-activating elements of a proof and steps in mathematical understanding. Like readers of novels, the mathematical reader performs the mental action of running through steps cued by a script, but since scripts deal with expected sequences of actions, the reader’s attention is particularly caught when a proof deviates from the expected background of mathematical scripts. By undertaking such narrative reasoning, mathematicians are prompted to focus on the novel, likely crucial, elements of a proof. Reciprocally, HPS analysts like Andersen can identify more precisely which elements count as most significant in mathematical reasoning and understanding, and for which kind of readers, since script-activation depends on a reader’s level of understanding of an expected situation. Notions such as scripts, narrative performativity and other ideas from cognitive narratology could similarly be applied to many domains studied by HPS scholars. Wise, for instance, broadens the notion of script to several areas of scientific knowing in his Finale to this collection (Chapter 22). But where such an approach might bear most fruit is in combined textual and ethnographic analysis, of the kind sketched by Andersen – specific elements of a scientific text can be connected to particular narrative-like reasoning, and that mapping contrasted with scientists’ own accounts, as well as analysts’ reconstructions, of scientific activity.

2.5 Conclusion

Narrative theory is an extensive and complex field and, in this chapter, I have only worked through some of its key concerns and ideas as they apply to scientific narratives. My aim in doing so has been twofold. On the one hand, I have sought to encourage HPS scholars to treat narrative in the focused, technical terms of narratology, by demonstrating the analytical productivity this promotes. Such analysis – as undertaken in the NS Project and chapters in this volume – reveals that a ‘mise en récit’ always involves an active component of knowledge-making or reasoning, even when a narrative (representation) is also the output of some scientific endeavour. Reciprocally, if narrative in science is always active, it is not an activity divorced from any concrete, material basis; a major part of the value of narratological tools is that they can serve to trace precise connections between narrative as text and narrative as mode of reasoning. What the NS Approach provides, then, is precision and rigour to an object of study – narrative – that otherwise risks overflowing its conceptual bounds to such an extent as to offer no meaningful basis for comparison or interpretation. NS offers exciting perspectives as an approach deployed alongside the usual epistemic resources of HPS.

On the other hand, this chapter elucidates the various ways in which work in the NS Project is informed by concepts from narratology, even where such concepts are not emphasized or delineated. As historians and philosophers of science, contributors to this volume bring a sensitivity to the theoretical and contextual constellations in which their case studies can be situated. Our studies thus bring a depth of detail to explorations of narrative in a non-literary domain – they can complement and complete narratologists’ investigations in this area with much-needed science-specific expertise. Just as I hope future HPS work will be open to narratological perspectives, I similarly encourage narrative scholars to draw upon HPS expertise, as showcased in this volume, in developing their field beyond the literary. This chapter has notably pointed to some distinctive characteristics of scientific narratives – their frequent non-human, even generic, protagonists; their iterations of story-making and discourse-configuration – as well as proposing that there is less of a divide between scientific and literary narratives than often assumed, when it comes to their situatedness in time – it is just that different questions of timing might arise. And, of course, there remain many areas of enquiry where collaboration between HPS and narrative studies would be fruitful: the affective charge of scientific narratives, forms of narrative focalization and the particular interplay of ordering and duration in work in the historical sciences, to mention just some I have signalled above.

But to conclude this chapter I would like to turn briefly to the ambitions held by narratology to be considered a science, from its pre-history in Russian formalism to its more recent cognitive turn.Footnote ⁶⁰ Could we apply the NS Approach to narratology itself? As Reference PuckettPuckett (2016) stresses, narratology as a domain of enquiry is not without its own history. Where he historicizes it in terms of key political and intellectual currents, we might ask how narratology is informed by other scientific fields and what role narrative-making plays in its endeavours. If we had to classify narratology, we could place it in the category of the human or social sciences, as taking a human product – narrative – and its cultural and social imbrications, as its object of study. We might then sketch a shift in perspective from a view of narratology influenced by the model of chemistry – with stories dissected into a fixed set of re-combinable elements – to one that enacts something of a convergence with cognitive science and some branches of psychology. Early structuralist Algirdas Greimas (Reference Greimas1983: 65), for instance, praised the language of chemistry as ‘a semiotic form which must, across all kinds of language, serve to express its meaning’,Footnote ⁶¹ while to read Manfred Jahn’s encyclopaedia entry (Reference Jahn, Herman, Jahn and Ryan2010) on cognitive narratology is to be plunged into considerations of ‘preference rules and processing strategies’ that would not appear out of place in a research article in computational science. By analogy with chapters in this volume, we might speculate that early structuralist narratology mobilizes ‘thin narratives’ of the kind identified by Paskins (Chapter 13), or that recent cognitive theories enlist strategies of ‘narrative performativity’ to provide imaginative support for their claims (as in the article investigated by Jajdelska in Chapter 18). What might such a transition imply for understanding the evolution or limits of narratology as a ‘historically specific logic’, to use Puckett’s terms (Reference Puckett2016)? When we apply a notion like the script to a scientific narrative, to what extent do we invoke distinctively narratological theorizing, as against ideas from the script’s origins in AI? Or, is to pose such questions to descend into a methodological spiral, where narrative and science turn circularly around each other?Footnote ⁶²