Numbers, words, and persons in intellectual objects

Why do we prefer numbers?

Re-Assembling Reality #27b, by David A. Palmer and Mike Brownnutt

A crucial intention behind the creation of intellectual objects is that they can be communicated so that, when the intellectual object enters the mind of another person, that person can reasonably be expected to be examining the same thing in their own mind. A reasonably reliable way to ensure that information is not lost in such communication is to embed the intellectual object into a physical object: a document, by means of writing. The written document then becomes an object that any number of people, even separated in space and time, can pick up, separate from its original context, turn over in different directions, pick apart, communicate about, and argue about.

This is in spite of the fact that, as we have discussed in Re-Assembling Reality #7, #11 and #12, the knowledge is not contained in the intellectual object itself: the communication of knowledge requires human engagement. In educational institutions, in order to be sure that an intellectual object is adequately transmitted, teachers have discussions with students about it, explain it to them, give them problem sheets, and take them out on field trips until the idea is settled in their minds. These discussions, exercises and field trips are designed to make students look at the object from different angles, make connections with other objects, and implant them into their memory.

If implanting an intellectual object in a book was a reliable way of reproducing the idea in someone’s mind, educational institutions would give people books and be done. Why do we go through all the time and expense of giving people problem sheets, explaining it, discussing it, and taking them on field trips to see it first hand? We do that because books are rubbish at conveying ideas! At least, they are rubbish at conveying the rich, thick ideas that are necessary to call anything “understanding.” The book gives the explicit knowledge. That is necessary, but it is not sufficient. The worked problems, the discussions, arguments, and field trips give the tacit knowledge.

Notwithstanding the role of personal communication in the generation and transmission of knowledge, scientific work is largely, if not entirely, geared to the production of intellectual objects. Each scientific discipline has its norms as to how intellectual objects should be constructed. To be trained in a specific discipline is to be trained in how to build an intellectual object according to the norms of that discipline.

In spite of all the differences between disciplines, there are some norms that run across most scientific disciplines, which are often the standard by which an intellectual object is perceived to be “scientific.” According to these norms, intellectual objects should be written in the most precise and logical language possible, so that any two minds reading the document will be compelled to undergo exactly the same mental operations, and to reach the same conclusions. Mathematics is often considered to be the perfect means of achieving such a level of precision. Scientists usually try very hard to turn things into mathematical objects.

Mathematical model of a non-collaborative urban goods delivery scenario, in which each company defines its delivery plan independently, in which customers are never shared and each company is just trying to minimize its own routing costs. Hence, each company individually solves itsown vehicle routing problem with vehicle capacity constraints for a local optimization.
Andrés Muñoz-Villamizar et al, “Non-Collaborative versus Collaborative Last-Mile Delivery in Urban Systems with Stochastic Demands.” Procedia CIRP 30 (2015) 263–268, from: https://www.researchgate.net/publication/276364999_Non-Collaborative_versus_Collaborative_Last-Mile_Delivery_in_Urban_Systems_with_Stochastic_Demands [accessed Jul 29 2022].

The ideal, “pure science” then, is one whose objects can be numerically measured and mathematically described, in order to attain the highest level of precision. And that is, when you think about it, strange. Because there are lots of things in the world that are not precise. Where is the edge of the hole in the ozone layer? Who knows. You can say precisely where the concentration drops to 50% of the historical seasonally adjusted average concentration. And that is a precise number. But who cares?

Perhaps a major reason that scientists (particularly in the life sciences and social sciences) want to turn things into mathematical objects is that this is what physicists do, and they want to be as cool as physicists.

Intellectual objects made up exclusively of words, on the other hand— such as the qualitative anthropological study of cosplayers described in Re-Assembling Reality #27a— are usually not seen as “hard” science, if they are seen as “scientific” at all.

And so, we have a hierarchy of scientific disciplines. Those whose intellectual objects are made of numbers are at the top, while those whose objects are made of words are at the bottom. And among those whose objects are made of words, there is a hierarchy between those that use impersonal language, and those that use personalized language. For example, consider this ethnographic vignette by the anthropologist Eduardo Kohn in his book How Forests Think, based on his research among the indigenous people of Avila, in the Amazonian region of Ecuador. This passage is written with the intent of compelling your mind to think the way he and his interlocutors were thinking while they chatted one evening:

Back at home, as they talked with Delia over bowls of manioc beer, Luisa imitated how through the bush she had heard the family’s dogs — Pucana, or Red Face, their favorite; Cuqui, her aging companion; and Huiqui — barking excitedly, “hua’ hua’ hua’ hua’ hua’ hua’ hua’ hua’ hua’, the way they do when they’re following game. Then she heard them barking, “’ya ya ya ya’”, poised to attack. But then something very disturbing happened. The dogs started yelping, “aya — i aya — i aya — i”, indicating that now they had been attacked and were in great pain.

“And that,”, Luisa remarked, “was it. They just fell silent”.

chun

silence

How could things have changed so suddenly? For the women, the answer turned on imagining how the dogs understood, or, more accurately, failed to understand, the world around them. Reflecting on the first two series of barks, Luisa remarked, “That’s what they’d do if they came across something big.” That’s what they’d do, that is, if they came across a big game animal. “Was it a deer they were barking at?” Luisa remembered asking herself. That would make sense. Just a few days before, the dogs had tracked down, attacked, and killed a deer. And we were still eating the meat.

But what creature might look to the dogs like prey but then turn on them? The women concluded that there was only one possible explanation; the dogs must have confused a mountain lion with a red brocket deer. Both have tawny coats and are approximately the same size. Luisa tried to imagine what they were thinking. “It looks like a deer, let’s bite it!”

Delia concisely summed up their frustration with the dogs’ confusion: “So so stupid.” Ameriga elaborated: “How is it that they didn’t know? How is it that they could even think [of barking], ‘yau yau yau’, as if they were going to attack it?

What each bark meant was clear, for these barks are part of an exhaustive lexicon of canine vocalizations that people in Àvila feel they know. What was less obvious was what, from the dogs’ perspectives, prompted them to bark in these ways. To imagine that dogs might fail to discriminate between a mountain lion and a deer and to trace out the tragic consequences of that confusion — the dogs just saw something big and tawny and attacked it — required thinking beyond what in particular the dogs did, to how it was that what they did was motivated by how they came to understand the world around them. The conversation began to revolve around how dogs think.” [1]

The information in this account could have been conveyed in more concise, impersonal language as follows:

The indigenous people of Avila have pet dogs. Their pet dogs hunt wild animals in the forest, but are sometimes hunted and killed by mountain lions. The indigenous people give different meanings to different dog barks. By listening to barks, they interpret what the dogs think. They believe that dogs can think and communicate their thoughts by barking.

https://freesvg.org/dog-reading

Kohn’s account is more literary, almost like a novel. It compels us, the readers, to imagine ourselves sitting in the evening drinking manioc beer with Kohn, Luisa and Delia, listening to the dog barks and cries, feeling affection for their dogs, and speculating with them as to what happened. While Kohn’s book is an intellectual object, it tries to bring to life the persons in the story, and to elicit our emotional reaction as persons. The second account, on the other hand, feels more “scientific”. It has stripped out the personhood of the ethnographer, the indigenous people, and their dogs, and it prevents us from responding as persons to them.

Our hierarchy of sciences thus places intellectual objects made with numbers at the top, intellectual objects made with depersonalized words at a lower level, and those made with personalizing words at a level so low that many would even question if it can count as science.

The Covid-19 pandemic mobilized scientists from all disciplines to use their own methods and theories to conduct research on various aspects of the virus and its effects. Let’s look at a sample of academic papers on Covid-19 from different disciplines. The papers have been ordered more or less according to the current hierarchy of sciences:

“A primer on using mathematics to understand COVID-19 dynamics: Modeling, analysis and simulations” (Infectious Disease Modeling).

“The flow physics of COVID-19” (Journal of Fluid Dynamics).

“Chemistry of Atmospheric Fine Particles During the COVID-19 Pandemic in a Megacity of Eastern China” (Geophysical Research Letters)

Pathogenesis of COVID-19 from a cell biology perspective (European Respiratory Journal).

“The Neurobehavioral Economics of the COVID-19 Pandemic: Consumer Cognition, Perception, Sentiment, Choice, and Decision-Making” (Analysis and metaphysics).

Studying the psychology of coping negative emotions during COVID-19: a quantitative analysis from India” (Environmental Science and Pollution Research).

“Towards a post-COVID geography of economic activity: Using probability spaces to decipher Montreal’s changing workscapes” (Urban Studies).

“COVID-19 as a Complex Intergovernmental Problem” (Canadian Journal of Political Science).

“COVID-19 and symbolic action: global pandemic as code, narrative, and cultural performance” (American Journal of Cultural Sociology).

“Distantly United: Papua New Guinean Relationality in the Face of COVID-19”(Anthropology Now).

At the top of the list are papers that use numbers to build intellectual objects, and at the bottom are those that use words. The papers at the top provide mathematical models of the virus, while those at the bottom use words to model how people act and relate to each other in the presence of the virus.

The distinction between numbers and words (also known as quantitative vs qualitative) overlaps with a few other distinctions:

The contrast between the two columns seems obvious (and is similar to the “two columns” of science and religion that we have criticized in the first essay of Re-Assembling Reality). But this division, and this hierarchy is not in any way “given”. There is nothing obvious or logically necessary about the progression from maths to natural sciences to life sciences to social sciences. And the idolization of mathematics is both a recent phenomenon and a culturally contingent one.

Flowchart of the new coronavirus transmission model with variables and parameters, from the article “Mathematical model describing CoViD-19 in São Paulo, Brazil — evaluating isolation as control mechanism and forecasting epidemiological scenarios of release” by H. M. Yang et al, published in open access in Epidemiology & Infection journal.

At various points in European history the making of a scientific apparatus was seen as a menial task, so experimental physics was looked down upon. At other times, occupations as unapplied as mathematics were seen as being of no use to society, and so frowned upon. Or, the applications were seen as primarily in magical arts, and more associated with sorcery than serious science. Similarly, being a medic (while an esteemed calling in the modern world) has, at numerous times in history been seen quite differently, as a menial task, a trade, a craft, or, at any rate, far from the elite and esteemed professions.

Many people today think in terms of a hierarchy between qualitative and quantitative sciences, but this is a contingent cultural construction, with scant connection to any necessity or reality. In the past there have been other ways of dividing branches of knowledge and other ways of placing them in a hierarchy, and in the future there could again be other ways of doing so too.

Today, the intellectual objects of modern science can be vastly different from each other, but they all have one thing in common: the higher they stand in the hierarchy, the more they strive to model reality without any resort to personal agents with consciousness and intention.

The cognitive scientist Robert McCauley has claimed that, “one way of characterizing the history of science is as a process that has, over time, steadily restricted the domains in which appeals to agent causality (of any sort) are any longer deemed legitimate, at least for the purposes of scientific explanation” [2]. What McAuley calls “agent causality” includes any causality attributed to persons as agents, and, he stresses, of any sort — including humans. In his narrative of the history of science, scientific progress is equated with a process of increasing de-personalization.

The directionality of the exclusion of persons over time is not a necessary one, but a contingent cultural construction. At best it is only contingently true. But it is not contingently true for all of history, nor for all science. It is contingently true for the history of Western science over the past two centuries.

[1] Eduardo Kohn, How Forests Think. Toward an Anthropology beyond the Human. Berkeley, CA: University of California Press, 2013, pp. 71–72.

[2] Robert N. McCauley, Why Religion is Natural and Science is Not. Oxford University Press, 2011, p. 117.

This essay and the Re-Assembling Reality Medium series are brought to you by the University of Hong Kong’s Common Core Curriculum Course CCHU9061 Science and Religion: Questioning Truth, Knowledge and Life, with the support of the Faith and Science Collaborative Research Forum and the Asian Religious Connections research cluster of the Hong Kong Institute for the Humanities and Social Sciences.

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David A. Palmer

David A. Palmer

I’m an anthropologist who’s passionate about exploring different realities. I write about spirituality, religion, and worldmaking.