The 2019 Journey in Science series at Rodgers Library for Science & Engineering at the University of Alabama:
I will give a lightening talk summarizing my past and recent research on the topic of American public opinion towards climate change. In this talk, I will discuss the various forces including both natural and socio-political ones that influence American opinion towards this critical issue.
While some federal agencies such as EPA and DOE are under increasing political scrutiny and pressure on their climate research and communication efforts, the National Academies of Sciences, Engineering, and Medicine as an independent entity is doubling down the effort to engage the public and decision makers on the scientific consensus of climate research. The Academies just launched a Climate Communications Initiative.
There has been a replication crisis in medical and psychological studies in recent years. This NYT piece documents a prime example in social psychology. At the center of the "drama" are Amy Cuddy whose TED presentation on power pose has attracted tens of millions of views on YouTube and several statistically savvy researchers including Andrew Gelman.
For many empirical scientists, using statistical analyses of a random sample to make inference for the entire population is the most reliable way to reveal some hidden patterns, except when a "pattern" already exists in the researcher's mind before even conducting the study. What the researcher needs to do is to find an ideal "path" to use the data to prove the preexisting pattern. This has been known as "p-hacking." (also read here, here, here,) Conducting research has never been easier. Scientists are "blessed" with so much data. With the blessing also comes a daunting task: correctly detecting signals from an expanding sea of noises. We empirical scientists thus have the obligation to constantly educate ourselves about the most recent advances in statistical methods. In the meantime, we need to constantly remind ourselves of putting aside our biases and wishful thinking while conducting research. Actions need to be taken at not only individual level but also collective level. Too much hype has been given to the so-called statistically significant findings. The glory of "statistical significance" has permeated the entire culture of science. Scientists are first and foremost humans who are driven by desires for success, fame, status, and respect. No one would pay much attention to a study that produces largely insignificant results. Maybe, incentives can be provided to researchers who after painstaking research design, meticulous data collection, and rigorous statistical tests end up with statistically insignificant results. I remember having an in-class discussion in graduate school. The professor told us that sometimes insignificant results can be meaningful too. Journal editors may want to give equal consideration to those rigorous studies that fail to produce significant results. While everyone is busy conducting original studies, incentives need to be provided to encourage replications. Only when we put checks and balances in place can we make this system more transparent and healthier.
Scientists have started brainstorming about a path forward in the wake of the replication crisis. Some suggest, if P-hacking is such a rampant issue, why not make it harder to achieve significance? This Nature Human Behavior article proposes raising the bar by lowering the P-value threshold from 0.05 to 0.005.
Each year before the announcements on Nobel Prize winners in October, scientists enjoy the prediction game. Like box-office grosses in the film industry, citation provides a reliable measure of impact and influence of scholars' work. The Clarivate Analytics uses Web of Science data to gauge scientists' impacts and identify potential winners. Since its inception in 2002, their record has been quite impressive: they have correctly identified 43 scientists who went on to win the Nobel Prize.
AI - artificial intelligence has become a buzz word nowadays. Geographic information scientists certainly don't want to miss this bandwagon. At the Esri UC, I have heard many talks on how machine learning can be utilized to identify spatial patterns and predict locations of events. With limited training data, the machine can detect certain patterns that may evade human minds. If used wisely, AI can help advance scientific knowledge by relentlessly pushing the boundaries. Science just published a special issue on this topic.
In a political climate that is increasingly hostile to American scientists, the french government is gesturing to them by offering 4-year grants worth up to €1.5million each.
Before March for Science, there was a debate about whether politicizing science would jeopardize scientists' reputation for being objective in their scientific pursuits. Early evidence suggests that the march did drive liberals and conservatives further apart on their views towards scientists. Whereas, their views toward science (research scientists conduct) have remained immune to change by this kind of publicity.
The concern for politicizing science is not without legitimate reasons. The scale of issues like climate change transcends personal experience with the immediate environment. Public understanding of this kind of issues thus hings upon multiple information sources. Unfortunately, scientists' peer-review articles are quite elusive for laymen to digest and they often stay behind pay walls. The media and others try to bridge the scientific community and the public, with journalists and others taking on the responsibility of translating scientific findings for the mass. With the third party being involved, things can get even more complicated. For instance, one principle called "balance" commonly adopted in journalism is intended to project a "fair" and "objective" image (Boykoff and Boykoff 2004). Guided by this principle, journalists in practice would interview one scientist whose view represents the majority's and one scientist whose view reflects the minority's. By doing so, both are given equal time on the air or space on the paper. Through this process, any scientific consensus would be perceived as "unsettled" by the receiving end.
Scientists are human beings and can make mistakes. The public trust in scientists is indeed found to be a powerful factor of converting knowledge about global warming into risk perceptions of this issue (Malka et al. 2009). My research demonstrates that people who believe that scientists make positive contribution to the well-being society are more likely to accept anthropogenic global warming (Shao et al. 2016).
Scientists are also perceived to have their own political ideologies whether or not this is the case for each individual. One of the implications of accepting human-caused climate change is governmental intervention, which is more in line with liberal worldview. It is therefore not surprising to see some critics perceive that climate change is "exaggerated (at best) or manufactured (at worst) by liberal scientists to force environmental action on the American political system" (Shao et al. 2016, 8). We actually found that "individuals who perceive that scientists are liberal are less likely to perceive that global warming is generated by human activity. This is in keeping with the perception held by some individuals that scientists are an ideological liberal group and that their findings are tainted by ideological bias" (Shao et al. 2016, 15).
Scientists really need to walk the fine line between pursuing scientific knowledge and helping the public understand scientific issues more accurately. If not done delicately enough, the public will dismiss scientists' work as "alternative facts."
Boykoff, M. T., and J. M. Boykoff. 2004. “Balance as Bias: Global Warming and the U.S. Prestige Press.” Global Environmental Change—Human and Policy Dimensions 14:125–36.
Malka, A., J. A. Krosnick, and G. Langer. 2009. “The Association of Knowledge with Concern About Global Warming: Trusted Information Sources Shape Public Thinking.” Risk Analysis 29:633–47.
Shao, W., Garand, J.C., Keim, B.D., Hamilton, L.C. 2016. "Science, scientists, and local weather: understanding mass perceptions of global warming." Social Science Quarterly. doi:10.1111/ssqu.12317
On Saturday, hundreds of thousands of people took their frustration with the current administration's anti-science attitudes to the streets. Given America's founding fathers' enthusiasm for science, it is safe to speculate that they would have joined and enjoyed the March yesterday.
This Saturday, on Earth Day, April 22 2017, tens of thousands of people will gather on the National Mall, and in dozens of satellite marches across the United States. During such a challenging time, evidence-based scientific approach cannot be more crucial to our sustainable existence. Please join thousands of nerds and science-friendly folks in the March for science. If you live in Montgomery, Alabama, the march will be in Oak Park - 1010 Forest Avenue from 10 am - 2 pm.