To save local news, bring down the cost
I recently watched the 5 pm news broadcast on NBC4 Los Angeles. There was a piece about expanding COVID-19 testing, another on a brutal crime with possible links to white supremacists and a segment on rising demand for food assistance. There was also weather, traffic and sports.
The hour-long broadcast required at least a dozen reporters, three anchors, countless producers, a few satellite trucks, even a helicopter.
The costs are staggering. If we cannot figure out a way to do local coverage for less, it will cease to exist.
The stubbornly high cost of local reporting is the through line that haunts Margaret Sullivan’s book, “Ghosting the News,” in which she recounts the withering of her hometown daily, in the successive waves of layoffs at local papers wrought by investor Alden Global Capital, and the ongoing struggles of so many journalists at small outlets. National news organizations have massive audiences from which they can derive subscription and advertising dollars to finance robust reporting. Local players, which, by definition, serve a small area, are shut out from these economies of scale.
From publicly available data to publicly accessible data
For the past two years, I have been working on a project called Crosstown that seeks to reduce dramatically the cost of producing local news while extending its reach. Our solution starts with data. We collect massive amounts of data about crime, traffic, parking tickets, vehicle collisions, air quality, building permits and so forth. Much of this data is publicly available but buried in hard-to-access government websites. Scrolling through it in its raw form is as gripping as reading the phone book.
Yet, if organized in the right way, it can unlock details about many of the core quality-of-life issues that animate good daily local news coverage. One of our reporters, for example, recently produced an astonishing insight: The Los Angeles Police Department is arresting more Black people for marijuana-related offenses now than it did in 2017, when recreational pot was still illegal.
Quarterly vehicle theft reports in Los Angeles, 2010–2020
We collect all this data in real time, and our software engineers built a method for sorting it by neighborhood and other criteria. Having it accessible in a digital, searchable system drastically simplifies the job of reporters and allows us to cover areas we never would have been able to previously. Reporters can browse a decade of data to discover which neighborhoods have the most bike accidents or which freeways have the slowest morning commutes. We used this system to figure out how much more trash Los Angeles residents are throwing out during the pandemic, and to show that car thefts have suddenly skyrocketed.
The data acts as a force multiplier, allowing us to move from local stories (Los Angeles) to hyperlocal (every neighborhood in the city). One story on home burglaries becomes 110 different stories about 110 different neighborhoods, each with specific info on the number of crimes in the community.
The best part? The costs don’t rise.
Certainly, there is much we cannot cover. The piece NBC4 did about a brutal hate crime had an on-camera interview with the victim’s relatives. It’s unlikely our small staff (two part-time reporters) would be able to pull that off. But we also do things that others cannot. For example, it took us less than a minute to determine that, despite a city-wide drop in crime during COVID-19 shutdown, the number of hate crimes had actually increased.
At times, our data even puts us out ahead of larger news outlets. For months, we’ve maintained a database on how many new COVID-19 infections there were in each neighborhood. We converted that into an interactive map that makes it easy for people to see how hard hit their area is. The map helped us identify early on a key trajectory of the disease: Wealthy areas of Los Angeles, which initially had the highest infection rates, had begun to flatten the curve, but infections in poorer areas were spiking. Others soon followed our lead.
Breaking conventions
In journalism, we’re attached to numerous conventions that define what quality news coverage “should” look like, from the anchor desk to the 800-word article. There are quotes from eyewitnesses, on-camera interviews with officials. But the inconvenient truth is that those conventions are also exceedingly expensive.
That’s why Crosstown has been searching for ways to automate as much of the reporting process as we can. Not because we prefer machines to humans. But because we realize that the journalists’ labor is precious and we need to keep it focused on high-level tasks, rather than busy work. Soon, we’ll be rolling out 110 different neighborhood newsletters, each with automatically formatted stories and charts. This will allow us to offer some level of coverage to every corner of the city with minimal extra costs.
We were able to create this process because we are based at a university, which gives us access to world-class software-engineering talent. Building the system was difficult, but now it almost runs on autopilot. Expenses are minimal and the reporters can focus on high-level analysis.
Our data-based approach to local news still allows us to hold power to account, and carry out many of the traditional responsibilities of the Fourth Estate. One of our reporters recently examined LAPD data to break down how much time police spend on non-emergency and non-crime-related work, even how often they break for lunch.
We used the same system to figure out where the most dangerous intersections in the city were located. And to determine that men caused most of traffic accidents (but were paying lower insurance rates than women).
Amidst the current industry-wide crisis, this type of data-driven news can fill in some of the rapidly expanding “news deserts,” places where local coverage has already dried up.
Scaling up local news
The low-cost system we have built at Crosstown in Los Angeles can be replicated in just about any city in the U.S. It could be slotted into an existing newsroom or could spring up in places where the local paper has closed shop (Youngstown, Ohio?).
Our goal is to create a Crosstown-in-a-box model that can easily be set up anywhere. With a reasonable upfront investment, we can deploy Crosstown’s software, mapping and data-sorting tools in a new city. Other newsrooms could use this to track the vital signs of their city, along with every neighborhood in it.
We know that if more journalists had the same easy access to data to cover their cities, they would break new ground and expand their reporting. More than a decade ago, Clay Shirky wrote “Newspapers and Thinking the Unthinkable,” that imagined a world in which papers disappeared. Though the title was grim, he was making the case for continuous, bold experimentation: “Nothing will work,” he wrote, “but everything might.”
Gabriel Kahn is a professor of professional practice at the USC Annenberg School of Journalism, and the editor of Crosstown.
