Is Your Data Naked? Objective Reporting, Data and Interpretation

I get a little worried when I see survey results naked in public.

One I’ve spotted recently: the Yale Climate Communications initiative publications on climate awareness. I LOVE their work, and stop what I’m doing every time I see a new release. It’s a fascinating combination of psychology and environmentalism...a social scientist’s dream.  I particularly appreciate the group’s framework of Global Warming’s Six Americas, which is an illuminating way of thinking about how people think about climate change…

…yet…

…sometimes their data is a little, well, naked. Objectively reported, with no dressings to spiff them up and let us know whether they are headed to the grocery store or the opera. Data without interpretation is tough for everyday readers to fully appreciate.

Most of us need the data analysts’ help in beginning to think about why what the data is showing is true. Not to mention considering the methodology limitations, self-selection bias, and unacknowledged variables.

In August 2024, Yale released a report that compared the differences in attitudes towards climate change among men and women—and among countries that are high per-capita emissions and income versus low per-capita emissions. Fascinating, right? Obviously both variables play a role in shaping a person’s attitude towards climate change. So what’s the problem?

By my read, the analysts who put out the article missed a great opportunity to discuss a consequential detail about the study’s methodology: respondents self-selected to participate in the survey based on receiving an invitation at the top of their Facebook News Feed.

In other words, the reported differences in attitude about climate change pertain only to active Facebook users—not the same thing as the general population.

In lower-income regions, those equipped to participate—with literacy, technical know-how, technology ownership, and internet availability—are often from middle to upper socioeconomic classes. This group likely has more awareness of global issues AND more resources (like money) to protect their families from threats.

Conversely, in high-income countries, those responding to such surveys might paradoxically be from lower-income segments, who are more directly impacted by and sensitive to immediate threats like cost fluctuations and severe weather. And who may be less informed about global events like the climate crisis.

In short, the fact that survey responses are limited to active Facebook users who were willing to click an ad MATTERS as a variable. It gives us an accurate picture, but not a complete one.

I’m not saying there isn’t value to raw data. But the richness is in the story it tells. The interpretation of the science, if you will.

That’s why you’ll often see me re-posting Yale Climate Communications’ studies with my own interpretation of their results. Sometimes the data requires very little contextualization to tell a very clear story, like when they surveyed Indians about their climate opinions.  But in many cases, diving into the whys and what-ifs brings color and meaning to what might otherwise feel like numbers on a screen.

I understand the choice to “let data speak for itself” in the interest of preserving an arena of objectivity, free from scientists’ assumptions and biases.

But I’d argue that naked data are ripe for misunderstanding, and scientists withhold our expertise and authority at the world’s peril.

Just like I rely on my CPA to interpret tax law, and my doctor to interpret public health policies for me, those of us fluent in climate have people leaning on us to help them understand what’s happening in this rapidly evolving landscape.

Helping non-scientists access and understand data isn’t an easy needle to thread. It requires a bit of interpretation. A touch of education. And yes, trust in our own ability to report objectively.

Keep an eye on my LinkedIn feed for my ongoing commentary of Yale and other institutions’ findings. And if you’ve got insights that you need to report objectively, bring ‘em over to Written Progress. We can get your reports dressed up and ready to go.