In a perfect world, having more science knowledge would predict agreeing with scientific consensus on an issue. However, a lot of research in science communication (and other fields) have shown that this is not the case. In fact, the more people know about a topic, the more polarized they become.
However, this may not be true for EVERYONE. That is, I suppose that people who have the most reason to disagree with scientific consensus will definitely find ways to do so; but, for those who don't care (e.g. political moderates, religious moderates), could we see a relationship between knowledge and acceptance of science information?
I was playing around with some data this morning from a project I am involved with in collaboration with Dan Kahan, Katie Carpenter, Laura Helft, Howard Hughes Medical Institute (HHMI), and Annenberg Public Policy Center (including my amazing fellow postdocs), that examines the relationships between science curiosity, evolution belief, and engagement with documentaries on evolution. This data was collected from a nationally representative panel by YouGov.
To get people's stance on human evolution we ask (near the end of the survey):
True or False: Human beings, as we know them today, developed from an earlier species of animals.
About 38% of our sample (N=2,500) answer "false" on this item, which is pretty consistent with other nationally-representative polls asking about evolution. For instance, a 2007 Gallup/USA Today poll finds that 44% of people polled say evolution is either probably or definitely false. A 2011 Fox News Poll finds that 45% of people polled say that the biblical account of the origin of human life is most likely true (compared to 21% support for the theory of evolution as outlined by Darwin). And a 2014 poll by PRRI/AAR Religion, Values, & Climate Change Survey find that 41% of people polled either mostly or completely disagree that evolution is the best explanation for the origin of human life on earth.
Importantly, all of these items specifically ask about the origins of human life. Recent research suggests that people are more likely to endorse evolution when thinking about the origin of animal and plant life.
The people most likely to be motivated to disagree with scientific consensus on evolution are those who are religious. Evolution is often contrasted with biblical accounts of the origins of human life such as creationism and/or intelligent design. For those who interpret their religious text literally, it is difficult to reconcile the theory of evolution with, for example, the account in Genesis. "
Thus, we wouldn't expect people who have strong religious beliefs to support the theory of evolution, no matter how much science knowledge they have.
Those who are not religious, on the other hand, have no reason to doubt the scientific consensus. So we wouldn't necessarily expect a correlation between science knowledge and acceptance of evolution there, either.
Where a relationship between science knowledge and evolution may exist is in the middle---those who are somewhat religious, but are not so committed to a literal biblical interpretation that they would reject scientific evidence. But on the other hand, they are not so quick to automatically accept scientific consensus as those who are not religious would be, because they have an alternative hypothesis that is supported by their religious in-groups. Thus, it is possible that we may see a relationship between accepting evolution and science knowledge here.
In our study, we used Dan's Ordinary Science Intelligence scale as a measurement of science knowledge. We also asked several items related to religiosity, such as how frequently people engage in prayer, how often they attend church services, whether they consider themselves "born-again", and how important their religion is to their daily lives. I combined these items into a index of "religiosity" using item response theory, which--when calculating scores of religiosity--takes into consideration that answering with higher values for some items (e.g., religious importance) are likely to indicate a higher level of religiosity than answering with higher values on other items (e.g., being "born again").
Then, I conducted logistic regression analyses in R predicting acceptance of human evolution (e.g., answering "true" to our evolution item) with ordinary science intelligence and religiosity as predictors.
The regression revealed an interaction effect of religiosity and ordinary science intelligence. To graph this, I grouped religiosity into four categories: people who were in the bottom 25 percentile on religiosity, 25 to 50th percentile, 50th to 75th percentile, and 99th percentile (top 25%).
The raw data points are "jittered" so that you can more easily see the density of responses around particular points. The lines represent the predicted probability of accepting human evolution contingent on your level of science intelligence. The percentiles, as I said above, represent people's religiosity.
You can see from the figure that science knowledge seems to predict acceptance of human evolution for people who are in the 25th to 50th percentile and for people who are in the 50th to 75th percentile. People who are in the lowest level of religiosity basically accept human evolution across most levels of science intelligence (discounting the small clump of participants who are really low on science knowledge). For people who are the highest in religiosity, there is no relationship between science knowledge and accepting evolution.
So, this data seems to show that knowledge *can* predict acceptance of evolution, but only for people who are not completely motivated to ignore scientific consensus, but have some reason to doubt it.
Measuring Climate Change Belief
For the past year (almost), I've been working with colleagues at the Annenberg Public Policy Center to examine how Pope Francis's encyclical, Laudato si: On Care of Our Common Home, may have influenced the U.S. public in terms of their climate change beliefs.
We used nationally-representative survey data (with an over sample of Catholic respondents) and had several waves of data collection. However, when we began looking at the data, we were frustrated: It didn't seem like anyone was changing their beliefs at all.
To operationalize climate change beliefs, we asked three basic questions (these questions are very similar to what is asked by other organizations that are measuring climate change attitudes, like Pew):
We standardized responses on these items and then created an averaged index and used this as our measure of climate change beliefs.
However, this scale is not normally-distributed. In fact, there is a huge ceiling effect: many individuals choose the strongest rating on all three of these climate change options. For instance, let's look at a table showing the frequency of participants (from our pre/post encyclical release panel, n = 602) among each level of position by each level of consensus.
I've bolded the number in the bottom right corner. Note that is NOT a total of the columns and rows. That is the number of participants who answer with the highest value on both the scientific consensus item and on the position item. It is important to note that these are the values for the items BEFORE the encyclical has been released. If we anticipate that the encyclical would have a positive effect, how are we going to measure that when a huge portion of the sample has hit the ceiling before the encyclical has been released?
To be fair, when most people are curious about whether the Pope influenced people's beliefs on climate change, they are not interested in those who are already climate concerned. Instead, we may want to see, for example, what climate change skeptics might think after they hear what the Pope has to say. However, it is likely that the Pope's messages will also influence those who already believe in climate change.
So how useful is our measure of climate change beliefs and did we really capture people's climate change concern at the higher ends of the scale? Moreover, is this why it appears that no one is changing their beliefs (when we look at the overall numbers, not broken down by previous beliefs or ideology).
To answer these questions, I used item response theory to examine our scale.
I chose to use item response theory to examine our scale as it allows us to examine how informative the proposed scale is at each level of the latent variable (also called "theta"). While some scales, like this one, have high inter-item reliability (Cronbach's alpha), they may be informative for only a portion of the scores along theta. For instance, item response theory shows that the Cognitive Reflection Task is only informative for people who score above the mean on the scale.
Eventually, I would like to learn how to run IRT in R, but for now, I'm using XCalibre. In XCalibre, I ran a polytomous Generalized Rating Scale Model (GRSM: Samejima, 1969; 1996), which is the most appropriate model to use when item responses can be characterized as ordered categorical responses, such as those for a Likert scale.
XCalibre provides output for both classical statistics as well as IRT parameters.
As predicted, our inter-item reliability is very high, Cronbach's alpha = .96. But this does not mean that our scale is informative across all levels of our latent variable (i.e., ccib, which can be conceptualized as climate change issue beliefs, climate change attitudes, or climate change concern).
Test Information Function
XCalibre provides the test information scores at every level of the latent variable theta. Then, the Test Information Function, is a graphical representation of how much information the test provides at each level of theta. You can see from the figure below that the information from our scale is skewed toward the lower scores, we don't get nearly as much information from people who are scoring at the top of our scale.
Category Response Functions
We can also look at the category response functions for each of the items that are used in our scale. These can be interpreted similarly to multinomial logistic function graphs. That is, we can see what the likelihood of each response is at each level of climate change concern.
Here is the category response function for the position item. As you can see, once you get above 0, the most likely response is 4 (climate change is human-caused). Between 0 and -1 on climate change concern, the most likely response is 3 (climate change is due to natural fluctuations), between -1 and -2 it is 2 (we don't know enough about whether global warming is occurring) and from -2 to the end, the most likely response is 1 (climate change is not happening). In other words, this item is great at differentiating people's climate change position below the mean on climate change concern, but not that great above the mean.
We see similar results with the seriousness item.
Like with the position item, once people are above about 0.5 on climate change concern, they become most likely to say that climate change is a very serious issue confronting the nation. So, we don't have any discrimination among participants who score above 1 on the scale.
Same with Consensus. Indeed, recent studies have aimed to examine whether telling people that there is consensus on climate change will increase their beliefs about climate change, but from our data, it appears that a lot of people already believe that there is consensus on climate change. Basically, everyone who scores above -0.5 on the latent variable is most likely to agree that scientists agree that global warming is happening and is human-caused.
So, while our scale has a strong inter-item reliability, it really could have used some items that help distinguish between the upper ends of the climate change scale. Otherwise, we can't expect to have room for people who start off as climate change concerned to increase their concern contingent on hearing about the encyclical and/or Pope Francis's views.
Again, this may not be too problematic given that we are most interested in the influence of the pope's messages on climate change skeptics; however this is likely the cause for some of the results that we have shown in our studies under review (e.g., people who are climate change concerned are most likely to maintain their climate change beliefs than to increase or decrease them after hearing about the Pope's messages).
What is GMO?
This is the first part of a two (or more) part post inspired by my intense irritation from watching Jane Goodall last night on Bill Maher.
From countless posts on facebook and twitter to general media coverage, it has become increasingly apparent that the public doesn't really know what GMO is. Because I'm supposed to be doing a hundred other things right now, I thought it was a great time to write a blog post on GMOs.
Let's start with some definitions
Genetically Modified Organisms: Regarding the technical definition, GMOs are any life form that has had at least part of its genome (or genes) intentionally changed. This does not include changes that happen in nature (such as those from natural selection, evolution). These modifications are made Through techniques such as (1) conventional breeding; (2) mutagenesis, or (3) genetic engineering.
1. Conventional Breeding - In conventional breeding, plants are artificially "mated" or "cross-pollinated" to try to create plants with more desirable traits. Famous botanist Gregor Johann Mendel, for example, discovered rules of heredity when mating different types of pea plants. this process has been used for tens of thousands of years. This is how we have edible corn as compared to its ancestor, teosinte. While often alluded to as a type of GMO by the scientific community, the public does not view plants created through cross-breeding as GMOs.
2. Mutagenesis - In mutagenesis, genetic mutations are initiated by subjecting plant genomes to radiation treatments, or by exposing them to toxic chemicals. [Side note: This is the process by which many a superhero has gained his or her powers]. One real example of this is the ruby red grapefruit. Dr. Richard Hensz at Texas A&M worked to create the reddest grapefruit possible through ionizing radiation. Despite the general fear that words like "radiation" and "toxic chemicals" create, crops modified through mutagenesis are ALSO not what is viewed by the public as GMOs.
3. Genetic Engineering - The most precise way of altering the genome of an organism is through genetic engineering (see image below). A specific gene or sequence of genes is targeted and either turned on, turned off, or exchanged. There are a few methods for how this is done, usually using "biolistic transformation (aka the "gene gun") or through agrobacteria-mediated transformation. You can read about these processes in more detail here. It is crops that are created through genetic engineering that are referred to by the public as GMOs.
Source: ISAA Mentor's Kit, 2003.
Types of modifications made through genetic engineering
In addition to knowing what we are talking about when we say "GMO", it is also important to know that there are different types of modifications that are made.
1. Pesticide/Herbicide Resistance
The most infamous genetic modifications and the ones most covered in the media are herbicide resistant or "Roundup-ready" crops. These crops are modified to be resistant to the active ingredient in Roundup and other herbicide products, namely glyphosate. Some believe (and probably rightly so) that this will lead to an increased use of pesticides. However, it is important to make the distinction that it is not the modification itself that is bad but the behavior on the part of farmers that is potentially leading to the increased herbicide use.
While this is the most common and infamous modification, it is not the only one. And before our society decides to ban ALL genetically-engineered products, I think it is worthwhile to actually KNOW what the different types of genetic modifications are.
2. Nutritional Enrichment and Toxin Reduction
Some crops have been altered to provide better nutritional content than its natural counterpart. For instance, the International Rice Research Institute (NOT MONSANTO), a non-profit research organization, developed golden rice two decades ago. The purpose of golden rice was to act as a low cost method of improving the lives of people in Africa and Southeast Asia who were suffering from vitamin A deficiency which causes blindness and in some cases death. However, anti-GMO groups broke into the IRRI's research facilities and destroyed fields of the crop.
Also, some crops have been altered to prevent natural, harmful proteins from being made. For instance, did you know that when potatoes are fried, they release a carcinogren called acrylamide? Acrylamide is easily absorbed through the skin and distributed throughout the body. it has been found to cause neurotoxic effects in humans and animals. Thus, occupational safety organizations (such as OSHA) have set exposure limits. Switching to the genetically modified version of the potato would help alleviate this concern.
3. Environmental Stress/Climate Change Resistance
Some crops are also being developed to tolerate climate-based stressors such as drought, frost, and nitrogen starvation. For instance, drought tolerant corn has already been developed and many other crops are under testing. Use of these crops may be particularly important given the anticipated effects of climate change, particularly in lesser developed countries.
4. Pest Resistance and Virus Resistance
It is important to distinguish between pest resistant crops and pesticide/herbicide resistant crops. Tobacco, Corn, Rice, and many other crops have been engineered to express genes that lead to insects and other pests avoiding the crop, thus DECREASING the need to use pesticides.
Similarly, several crops have been saved from viruses that in some cases may have lead to the extinction of the plant and the destruction of the economy. For instance, in the late 1990s, there was an outbreak of the papaya ringspot virus in Hawaii, which threatened not only the crop but the entire industry and many jobs.
What genetically-engineered crops are on the market in the United States?
My final point for this post is that the public does not seem to know WHICH crops have been genetically-engineered, what crops are GMOs. In fact, articles have popped up claiming that gluten intolerance could have been instigated by the use of GM wheat (which does not exist on the market).
Here is a list of crops that are currently on the market as well as crops that are under evaluation or otherwise in the approval process
Currently on the market in the U.S.
I hope that this is helpful. I'll aim to post the next part of my blog on science consensus soon.
When Dan Kahan went to respond to my last post, we found out that Yale does not like the website I use to create my blog (Weebly).
So, instead, he replied via email and I have pasted his reply below. In his reply, he references a few of his posts--but mainly this one, as well as a few research articles.
I agree, of course, that someone can "get" the logic of an argument w/o accepting the conclusion b/c he or she doesn't accept the premises. That could be an explanation of how a non-believer in evolution passes an evolution exam. Maybe that was Aidan in the Hermann study.
Can you have knowledge without belief? I don't know. An admittedly oversimplistic thought exercise.
Dan Kahan and I have been ruminating on this question (as have many of his blog followers and the students of his Science of Science communication course, both virtual and in situ.
First, some (loose) definitions and a chart:
In this chart, belief and disbelief are independent of what is true in the world [although I recognize that there is—or at least should be—a higher likelihood of belief in what is known to be true in the world and disbelief in what is known to be false].
Before I start thinking about tricker topics such as climate change and evolution, I’d like to focus on a simpler model. So, for example, let’s consider whether or not X is a rectangle.
Premise: X is a rectangle:
There are two possible states in the world. One in which X is a rectangle and one in which X is NOT a rectangle (columns). Moreover, I can choose to believe that X is a rectangle or that X is NOT a rectangle (rows).
If X is indeed a rectangle, and I believe that to be the case, then I hold a true belief. If it is a rectangle and I do not believe that to be true, then I have incorrectly rejected that premise. Similarly, if X is not a rectangle (maybe it is a triangle), and I believe it is a rectangle then I am holding a false belief. If it is not really a rectangle and I do not believe it is a rectangle, then I am correctly rejecting that premise.
So, let’s say I am being taught the premise X is a rectangle. I’m given the following argument:
It is possible for me to have knowledge about the argument—I can learn the two propositions that lead to the conclusion. If someone asked me what is the argument for X is a rectangle, I could then give them the above argument. Importantly, I can do this without accepting the premise that X is a rectangle. That said, Is it possible to have knowledge about rectangles and X without accepting the premise that X is a rectangle? (Open Question)
Now, if I know the argument, then under what circumstances would I choose NOT to believe that X is a rectangle?
I would think that in order to NOT believe that X is a rectangle, I would have to reject one or more of the propositions in the argument. In other words, I’d have to believe that Proposition A is false and/or that Proposition B is false. It would not make sense to accept the two propositions but reject the premise.
Why would I reject one of the propositions?
A. Lacking Knowledge/Holding Misconceptions.
Distrust would occur in cases in which I doubt the information that I received about the propositions (or about information pertinent to the propositions)—whether I received the information though my senses (perception) or others’ testimony.
So far, my thinking is that it is possible to know the argument without believing, but I’m not sure if it is possible to have all relevant knowledge without believing—and people may lack all relevant knowledge because they distrust who its coming from.
Admittedly, this rectangle example is much simpler than complex scientific premises like Evolution and Climate Change. If we were to think of those theories as structured like big complex logical arguments, each of the propositions may be subpremises with their own set of propositions, and on and on. Is it this complexity that leaves room for cognitive dualism? If we prodded more deeply would we find that they are simply lacking knowledge or exhibiting distrust?