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Thoughts on Translation Tools, Expertise...and Italy

I recently spent 12 days vacationing in Italy with my mother and two older sisters. While my body is still processing large quantities of delicious cheeses, pasta, and gelato, my mind is digesting the experience of touring a foreign country with different norms, cultural nuances, and of course — a different language (though the diversity of head scratching bathroom set-ups also bears mentioning). On this trip, translation was always on the brain: translating my thoughts to others and in turn trying to understand the information presented to me, whether on signs, at train platforms, or spoken by short-tempered wait staff. Because despite my half-hearted attempts at learning Italian with the DuoLingo language app, or my high school courses in the nearby romance language French, I was nearly useless in speaking or understanding Italian.

The Need for Translation

My week plus of translation needs in Italy got me thinking about the role of translation in biology and, in particular, in genetics. In both contexts, translation carries at least two main functions: (1) operationalizing and (2) meaning-making. Operationalizing means to make functional, or to make a thing do.  Translation is a key term in the Central Dogma of Biology. DNA isn’t terribly useful just sitting all spaghetti’d up in our cells. Rather, DNA carries instructions on how to make proteins that build us and do most all the work in our body (this is DNA as the “instruction book” or “blueprint”). The Dogma states that DNA gets transcribed into RNA, a molecule very similar to DNA but more easily accessed by other cellular machinery. Then RNA gets translated into protein, going from a nucleotide code (the A’s, C’s, G’s, and T’s – actually U’s, for RNA) to a chain of amino acids that gets all folded up into a beautifully complex protein. Translation is the operationalizing of DNA, the process that makes it do.

The Central Dogma is great and all but it’s a process scientists have understood for about half a century now, so not exactly breaking news. The challenge currently facing genetic researchers is truly understanding what different variations in genetic sequences actually mean for people’s health and well-being — and perhaps their identity. Here the challenge is translating knowledge of DNA sequence into actual meaning. Perhaps into meaning for an individual patient and their health care provider making a treatment decision. Or perhaps meaning for a large group of people by better understanding how a disease or other biological process works. The questions are more than just what changes in DNA do to proteins, which could take us back to that literal translation step of the Central Dogma. The questions spiral out: only ~3% of our DNA codes for proteins, but all that non-protein coding DNA could affect other things like regulation or as yet undiscovered cellular processes. Also, our genetics interact with other things in our bodies and in our lives, further complicating the meaning-making part of the translation puzzle.

The Tools of Translation

My needs for translation in Italy were pretty much the same: to be able to do things and to make meaning. I am not an expert traveler nor linguist, but I did have some amateur tools at my disposal. First and foremost: on my smartphone, Google Translate (with Italian downloaded for offline use) and an Italian phrasebook app. Off the screen, my sisters and mother who had also done some DuoLingo lessons, and my occasionally useful knowledge of French. Google Translate, which I used quite frequently, would often give me incomplete information — sometimes a word wouldn’t translate, or it would give me something I had no idea how to pronounce (and the audio pronunciation isn’t available offline). I knew some of the rules, for example: “ch” is a hard C, as in chianti, while “ci” is the “chuh” sound, as in ciabatta bread. But usually I was moving through the world with partial information, still enjoying myself and interacting meaningfully with my surroundings.

Cherub in Scuba Mask
Cherub in Scuba Mask: street art I saw while in Florence, Italy.

I bring up the amateur aspect of my translation experiences in Italy because I see parallels with the phenomenon of consumer genetic testing. While scientists are still wrestling to make meaning of human genetic variation, consumer companies have gone ahead (some would say prematurely) to make interpretations of personal genetic data available directly to consumers. The majority of these consumer genomics customers are, like I was with Italian, not specially trained to interpret or filter genetic information. Yet if given some tools and some rules, they can probably navigate the unfamiliar territory with some degree of enjoyment and success. Sure they might make a wrong turn or get caught in a tourist trap pizzeria (darn you Piazza della Signore in Florence!). But should they be denied access for their lack of expertise, or for being only armed with some amateur and partial tools of comprehension?

Of course in my Italy metaphor the answer is “No!”, but I recognize that consumer genomics is more complex — and newer, which makes it harder to identify and weigh potential risks and benefits. Should access to personal genetic data be limited to specialists? Should specialists make better tools to enable amateurs to pursue their own translational and meaning-making activities? Tourists have been bumbling around foreign countries since there was bumbling to be had: that’s just part of the human experience. Is bumbling around our own genomes also going to become part of the human experience?

Mapping Metaphor across Big Data, Biotechnology, and Genome Sequencing

Everyday metaphors

Before I was geeky about science I was geeky about words. For my 16th birthday, my best friend gave me the “Encyclopedia of Etymology” — a giant tome about the origins of words (not bugs, people! That’s entomology). So of course I get excited when science and language interact, which happens a lot with metaphor. I even did my Master’s research thesis about metaphor (more on that later). One of the most surprising things I learned early on in that project was that most metaphor is actually lurking beneath the surface of how we talk and think on a daily basis, rather than being mostly confined to speeches and fancy poems (e.g., “Shall I compare thee to a summer’s day?”).

An example of a quite basic metaphor is that up is good and down is bad. Would you rather have things “looking up” or to be “feeling down”? Granted this metaphor may not hold across cultures, but in Western societies it is so ingrained as to almost be invisible. Note I did not discover all of this, but rather was introduced to these ideas in Lakoff and Johnson’s seminal 1980 book “Metaphors We Live By”. Think of Lakoff and Johnson like the Watson and Crick of modern metaphor studies. (If there is a Rosalind Franklin out there in this analogy, then my apologies in advanced for the omission!)

Metaphors for “big data” – h/t to Sara Watson

Metaphor is subtly sprinkled throughout our daily speech, and it can have powerful effects on how we think and act. Which is why it’s so important to identify metaphor and understand its sway on us. So I was pleased to recently come across self-proclaimed “technology critic” Sara Watson’s article on dominant metaphors for big data. She does a lovely job of breaking down dominant industrial metaphors for big data and suggests that replacing them with embodied metaphors, those more tied to our lived experience — our physical bodies — might help people exert more control over data and its downstream uses.  Otherwise big data becomes this inevitable industrial, machine complex bearing down on us, so better hop on board or get out of the way.

Today’s society has a borderline morbid fascination with big data, which I’ve also written about previously in “Big Data, Big Deal?”, and you can see how the dominant metaphors perpetuate this fascination.  A particularly problematic metaphor in my mind is that of data as a natural resource that should be mined, extracted, and purified. In this construct, data are commodified and spatialized. Just think of all the untapped reserves of “raw” data waiting for the boldest and most pioneering person to tap into: data logged daily by our smartphones, our Facebook profiles, and even our very bodies. In this metaphor, data become pre-factual and given, rather than contextual and imagined (whereas in actuality you have to conceive of something as a data point before you collect it — aha, even there,  I did it: “collect data” as if I was picking wild huckleberries on a mountainside…which I recently did, incidentally). But full circle back to etymology: the very word “data” is from the Latin verb for “to give”….so it’s not totally our fault that it’s easy to take data as “a given.” (More on other cool things you can learn about the word “data” in my earlier post.)

The need to tease out metaphorical concepts

Sara Watson’s article articulates metaphors as “metaphorical concepts”, or “X is Y”: e.g., “Data is a natural resource.” Formulating metaphor this way is helpful in understanding the consequences or “entailments” of the metaphor and to raise further questions. If data is a natural resource, is it a renewable one or something finite (e.g., fossil fuel) that we may run out of? If data is a natural resource, who is “mining” it and who is using or buying it?

Metaphorical concepts are rarely stated outright, but identified through analyzing different expressions of the metaphor. You can see these expressions listed under the heading of the metaphorical concepts in Watson’s article: words like “raw,” or “trove”. Analysis of metaphor involves picking out those instances and then drawing out the underlying metaphorical concept.

Critique of a CRISPR metaphor analysis

Metaphor analysis that stops short of articulating metaphorical concepts is less useful. Last fall I wrote a piece along with two of my thesis committee members critiquing a metaphor analysis of the gene-editing system CRISPR that had this very problem. We argued that failing to articulate underlying metaphorical concepts resulted in a missed opportunity to understand who uses CRISPR to do what? Is CRISPR, as a technology, the subject of the metaphor or is the scientist using CRISPR the subject? It’s an important question of who or what has the agency to act and make decisions about gene editing.

Also, because the authors didn’t identify metaphorical concepts, most of the metaphors they report were about the genome itself rather than about CRISPR. It would have been easier for them to draw robust conclusions about CRISPR metaphors if they’d been able to separate out genome metaphors (to separate the “text” from its “editor,” as we allude to in the title of our critique).

Metaphors about genome sequencing: my MPH thesis

Oh – and did I hear someone ask about my Master’s thesis? I’m going to assume that’s a “yes.” For my Master’s in Public Health degree in Public Health Genetics, which I completed Spring 2014, my thesis project was a metaphor analysis of research participants discussing whole genome sequencing. I was fortunate enough to have access to several transcripts from previously conducted interviews and focus groups where people were asked to discuss genome sequencing in the context of research and medicine. No one was asked about metaphors specifically, but because of the frequency of underlying metaphors in spontaneous speech, instances of them popped up often in the participants’ discussions.

One of the most common metaphorical concepts I identified was “Genetic information is a weapon.” In some cases, getting personal genetic information was seen as a weapon in the hands of the individual, something empowering them to act, to defend themselves against disease or other potentially negative experiences. For other people, the weapon metaphor was one where genetic information was used as a weapon against them, to knock them over or leave them “shell shocked.” So even the same metaphorical concept can have different  consequences, here depending on what  or who is in control of the information.

Full disclosure was that initially I wasn’t forming my results as metaphorical concepts (“X is Y”) but more like keywords or domains (as we later critiqued in the CRISPR metaphor analysis). My committee member and resident metaphor expert, Leah Ceccarelli, strongly encouraged me to find the metaphorical concepts. My only real objection was “that sounds hard” (remember I’d never done formal metaphor analysis before), so once I realized that was lame I made myself do it – and ended up with a much stronger project for it.

You can read my whole thesis on ProQuest: search for title “Mapping Metaphor: A qualitative analysis of metaphorical language in discussions of receiving exome and whole genome sequencing results” (or, if you don’t have access to ProQuest, I’m happy to email it!). I also had peer-reviewed journal article published here. (Yes, it took an extra ~18 months to have that paper see the light of day – see my earlier discussion of the iterative and often trying nature of scientific publication here.) Meanwhile, here’s a table summarizing the main metaphorical concepts I identified.

Table of metaphorical concepts from my thesis research project, with one or two example quotes from focus group and interview participants.
Metaphorical conceptExample quote(s)
GENETIC INFORMATION IS A TOOL[Getting genetic information] “might just be one additional piece of information to add to the toolbox”
GENETIC INFORMATION IS A WEAPON[Receiving genetic results for a child] “could be a piece of information for them…to have in their arsenal for decisions that they’re going to make in their lives”

“So you don’t want too much information and, and with, I think with this, it’s so much. Genetic, there’s so much out there, you don’t want to be bombarded either.”
GENETIC INFORMATION IS LIGHT[Receiving positive results, e.g., about athletic ability] “would be like hey there's a light in the end of the tunnel”
GENETIC INFORMATION IS DARKNESS“To know that I would develop early onset Alzheimer’s or, or something like that, I think it would be a consistent cloud over my life”
GENETIC INFORMATION AS GOODS INSIDE A BOX“I’m going to want to [get] results on all of them. I’m curious like that. But I’m…not very confident. Kind of like opening Pandora’s box, do you want to know what’s inside?”

[On choosing when to receive results] “I want to open that box that’s, that’s mine.”
GENETIC INFORMATION IS A PICTURE“I don’t think I’m closed out to anything. I, I like the good and the bad because it all makes the whole picture.”
GENETIC INFORMATION IS A DOCUMENT“If there was an architect going through the neighborhood and they were drawing plans, I want a copy of the plans of my house… I’m not going to build a house, I just want it.”

“…it would be nice to know, I guess I’m thinking of credit score like, here’s your credit score and here’s how you can improve it.”

Other recommended reading:

Ceccarelli, L. (2013). On the Frontier of Science: An American Rhetoric of Exploration and Exploitation. Michigan State University Press.

Condit, C. M. (1999). The meanings of the gene: public debates about human heredity. Madison: University of Wisconsin Press.

Lakoff, G., & Johnson, M. (1980). Metaphors We Live By. University of Chicago Press.

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