That gets right into the issues that Sir Albert Howard was bringing up in my previous comment. And it goes even deeper than that. Besides the issue of "test plot or actual farm?", you have to ask the questions:Consider the question “Are genetically modified crops more productive than conventional crops?” Some researchers prefer to answer this question by looking at field trials that allow variables like weather and soil type to be carefully controlled. Others prefer surveys of actual farms, because they reflect real-world variability. These two approaches often yield contradictory results, and there is no way of adjudicating based on the data which of the two provides a better guide to the future.
1) Do you measure productivity by total weight of crop, or # of calories actually contained in that crop?
2) Or do you need to go further and measure the full nutritional value in the crop by chemical analysis?
3) Or do you need to go further and measure the actual effect of the crop on the animals/humans it is fed to, and look at their health, which is what you're really trying to promote in the end?
Because if "productivity" is simply measure by crop weight, but your methods of productivity (like more and more chemical fertilizers that simply promote growth without adding full nutritional content) result in a less quality product, do you have an issue? If your genetic engineering makes a bigger rice grain whose nutritional value has been thinned out because you didn't actually change the amount of nutrition in the soil at all, then what have you gained?
And on top of that, there's the question of whether the PRODUCT is the only thing to be measured. Other questions that often fail to be addressed:
4) What if one methodology produces equal or greater crop weight, but only at the cost of depleting the soil, so that your soil fertility will run out and the land will become barren in 10 years?
5) What if one methodology is heavily reliant on the extreme use of limited resources like fossil fuels or water, and thus only elevates crop loads by depleting other resources?
6) What if one methodology results in dramatically more air or water pollution, or is more destructive to biodiversity in the surrounding area, or results in more diseases or pests in the long term which then need to be controlled by more antibiotics or antifungals or pesticides, and all those additional issues have a negative effect on the environment and the surrounding human community and the consumer?
7) What if one methodology is reliant on inputs that have to be imported from other areas, which decreases the self-reliance of the farm AND makes it vulnerable to interruptions due to issues on the other side of the world AND possibly depletes those other regions of their own resources?
8) What if one methodology increases crop numbers at the cost of progressively weaker and weaker seeds, so that the varieties "run out" after a few decades and new strains constantly have to be developed to replace strains that no longer produce?
9) Finally, since real humans (and possibly real animals) work the farm, what if one methodology is simply less enjoyable and fulfilling to the humans working there, which reduces their quality of life, which reduces the quality of the product they produce, and may even lead to them leaving the field altogether?
Just by looking at this one example, you can see how "laboratory science" or "test plot science" can fall short in so many ways of helping you understand what will actually help the real world move forward. In terms of agricultural science, the smallest unit that can really be meaningfully studied is the whole farm (if the farm is a self-contained unit where the animals and humans involved build and consume their own produce and then re-fertilize the soil with their waste), and even then you really are best served by looking at the surrounding community as well, because nothing is truly self-contained. And it takes a LONG time to see where all the possible effects will lie. If your farm is importing things from other communities and nations and continents, then you need to look at the effect those extractions are having on THOSE communities as well.
You can run thought experiments to see how this applies to many other fields as well. Cancer researchers, for instance, probably won't accomplish a lot without working with actual cancer patients....and treating the patient as a whole person, in fact, maybe even needing to look at the whole family.* Those who study animal taxonomy via genetics (or morphology or anything else) need to get out of the lab with their limited and isolated individual samples, and need to look at the actual communities in the field or they're going to keep producing patently stupid results. And so on and so on.
The A.J. Kumar example in the article is a perfect example of someone doing this well:
Or maybe just send them to the Peace Corps before they go to graduate school. At least that’s what A. J. Kumar did, after getting his undergraduate degree in physics at Stanford. Working in a small South African village for two years, Kumar began to see science as a way to leverage his impact on the world, and this made him skeptical of the culture of the lie. Like Marqusee, Kumar understands and appreciates the role of fundamental science, but he also recognizes how the logic of the lie justifies “digging down deeper and deeper on a single subject without stopping to ask why we’re doing it in the first place.” He thinks there’s “room for more intentionality in how we do science.”
In the applied physics Ph.D. program at Harvard, Kumar started with an interest in linking science to health care needs in poor countries. He quickly focused on a specific question: “How do we bring the information that we get from studying blood into low-resource settings?” The question pushed him in two directions: into the social context, to see what needs could be met with better information on blood; and into the science, to see what theories and tools could provide that information. So he talked to doctors who had experience working in Africa, and he talked to scientists in his lab and elsewhere, and this eventually led to a convergence between the two: a technique to separate proteins using a simple type of centrifuge that had been around for fifty years. This technique could be used for separating blood cells, which could potentially help diagnose sickle-cell disease, a health problem that lacked a quick, cheap, portable, and reliable diagnostic procedure. Kumar wraps up the story with modest alacrity: “So we were able to get some collaborators, start researching, doing the first experiments, and getting initial positive results,” showing that sickle-cell could reliably be diagnosed by density separation. “This allowed us to really charge forward and start the quest for funding, clinical validation, and trials, which took up the rest of my Ph.D.” The test he came up with can be done on-site in fifteen minutes, and it costs less than a dollar. Kumar was a one-man medical-industrial complex, coordinating all aspects of the research process, including commercial development, and using technological performance as a ruthless arbiter of scientific progress. In short, he made his research accountable to the end-user rather than to his scientific peers.
* If you don't understand why looking at the whole family when developing a treatment for a cancer patient is important, then ponder this penultimate paragraph of the article:
But Fitzpatrick also wonders if biomedical science undervalues other kinds of research that could offer solutions to pressing problems. “There’s not a lot of research on how best to socially, emotionally, environmentally, support Alzheimer’s patients, that might ameliorate their own anxiety, their own stress — maybe the disease, as horrible as it is, would be less horrible through a better care structure, but we do very little research on that.” Perhaps for now, research to help people with these diseases ought to aim at more practical questions. “I don’t think you can tell people ‘Well, we’ve got another forty years of research that we’re going to have to do’ when we also don’t know if there are better ways of supporting people.” And maybe in the process of understanding how better to help patients, scientists will discover things about the course of the disease and its varieties that can lead to effective therapies.