The Fiat News Index: Measuring How Media "Tells You How To Think" About News

Authored by Rusty Guinn via,

Now before we do this, let’s go over the ground rules. Rule Number 1: No touching of the hair or face.  

Most criticisms of the media – especially those popularized during the “Enemy of the People” phase of the Donald Trump presidency – have focused on assertions of its bias. Bias certainly exists, but we’re not here to adjudicate that. We think identifying bias is very hard to do so systematically. It is even harder to do without injecting our own biases into the creation of whatever system we might use.

Fortunately, the concept of fiat news we so often write about isn’t really about bias – or at least, it’s about far more than bias. Fiat news is about the press telling you how to think about issues. Fiat news is about the presentation of opinions as facts, regardless of whether they consistently favor one group or another. If you want a bit more of a primer, including why we call this fiat news, the original piece Ben wrote in 2017 is located here.

We think there are some ways to measure this, so we’re going to try. And we’re going to do it in the open. Let me introduce you to the Fiat News Index.

I’ve selected 20 of the largest and most prominent US-based news and commentary organizations. Using the tools and database from our friends at Quid, the Index measures the proportion of articles from a media outlet which use one of a range of words or expressions I selected. These words and expressions fall roughly into three categories: words that convey a causal link between two statements (Causal Expressions), words that seek to communicate the Common Knowledge element of a narrative (Common Knowledge Expressions), and words that communicate explicit value judgements (Value Expressions). These concepts will be familiar to readers of the recent In Brief, The Tells of Fiat News.

The basic idea behind this framework is that writers, when using Causal Expressions, are communicating how you should perceive the relationships between facts and other facts, or between facts and certain conclusions and analysis. This conflation is a common way to present a judgment or opinion as objective fact. It is a writer coaching you on the logical path they wish you to follow. Sometimes that is innocuous, because sometimes the relationship between two ideas, two facts or two statements really is incontrovertible. Often it is not. When using Common Knowledge Expressions, the writer is encouraging you to think less critically about an assertion or argument. It is, after all, obvious to everyone else. Value Expressions are more straightforward and easily understood. They also look a bit more like an analysis of bias, although these words may just as easily be used to tell you how to think about what is good and what is bad without any element of structural favoring of one point of view.

I suspect you could come up with many more such expressions. The danger to adding too many is that you end up with Type 1 errors, where we catch more innocent uses. News articles include quotes from subjects that include these terms, for example. And it’s not as if every use of these words in a news article can or ought to be avoided. In addition, the preferred style of different venues will be more or less likely to lean on these expressions. For this reason, the absolute levels are much less instructive than the relative levels. For me, I understand this index to mean, “If I open the pages of this publication, how much more likely is it than in another publication that I will read a story that is telling me how to think?”

Here is the Fiat News Index for the last 12 months ended November 10:

A few words. First, the Index includes four media companies that are not news outlets. This is by design. The unit of the Fiat News Index is the Vox, not because there’s necessarily anything bad or dishonest about what Vox does, but because Vox’s stated mission is to explain the news. Approximately 91% of its articles in the last year included one of these explainer words. Nothing necessarily wrong with that in a commentary or analysis publication (like Vox, The Atlantic, National Review or The New Yorker), but potentially a matter of concern when it takes place in a news outlet. Each other source is scaled to express how many Voxes of explaining their articles have engaged in over the last year.

The poles are instructive. On the one hand, we have Vox, and on the other, Reuters. In between, there is a meaningful range. While I don’t have the data to give Reuters a completely clean bill of health, for our purposes I think it is useful to think of their level as a baseline of the innocuous usage of these terms. From there, Voxes will rise with the (1) use of these terms to explain topics in news articles and (2) the relative proportion of opinion and commentary to pure news coverage. The first is our primary focus, but the second isn’t irrelevant, and we don’t consider it a false positive. You should read this as an attempt to proxy the following question:

If I open this publication, how likely is it that I will be told how to think about world events instead of being given simple information about world events?

It is possible, as noted previously, that some publications have adopted or prefer a simpler style that is less likely to use these terms in coverage. If you want to see that as a potential flaw, go ahead. I don’t want to tell you how to think about it. But I will anyway. I believe that the conscious choice by some venues to use less complicated language and sentence construction is a similarly conscious choice to keep reporting confined to explicit facts. As with so very many things, we might reasonably consider the New York Post the exception which proves the rule.

You will note two very glaring omissions: two massive publications, Fox News and the Wall Street Journal. This is a data issue on our end. We are working to resolve it. But a point of emphasis that is worth highlighting: this Index is not a measure of political bias. This Index is not intended to be a measure of political bias. Transparently, I still rather strongly expect to find a higher than average Index for Fox News once we can update our database. But in the meantime, we are hopeful that this proves useful to you in making up your own damn mind about what the news means. Doing so will play a critical role in our conscious efforts to resist both narratives and the exploitable memes which infect each of our minds.

We will continue to update this over time. We plan to research topic-related tendencies and add additional venues.