Deep Dive – Evolving Standards

I spent years teaching students the fundamentals of journalism so that they could create high-quality newspapers, magazines, and yearbooks. Before that, I was a student journalist myself, writing for my high school and college newspapers, eventually becoming editor-in-chief of the former and an associate editor for the latter. Now, I’m part of a small team developing code and providing digital support for a nationwide network of news websites.

While I’ve mostly used this website (which, I should note, represents only my own personal opinions and not those of my employer) to talk about tech, I think I’ve made it clear that I love participating in and thinking about journalism. So today, I’d like to present the first of what I hope to be a continuing series of Media Deep Dives, where we’ll take a look together at something out there in the news sphere—an article, photograph, etc.—and consider what makes it tick or examine its broader implications for the practice of journalism.

For this inaugural installment, which I’ve decided to split into two parts, I’d like to do both while sharing a story from The Washington Post about police departments that have found ways to skirt local bans on the use of facial recognition technology. While the story initially caught my eye thanks to my interest in AI ethics, I’m going to mostly set those issues aside. Instead, I’d like to start by exploring what this article shows us about the evolving nature of headlines. Then, in part 2, we can take a look at how this story exemplifies some of the debates around objectivity in journalism.

  1. Headlines in the Digital Age
  2. Objectivity vs. Neutrality

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Extra Credit: Displaying the top score in a popular word game

For good reasons, the New York Times does not openly publish the total possible points for its daily Spelling Bee puzzle. But when my partner and I play the game, we like to figure it out anyway and then see how close we can get. This is a well-defined task with well-defined inputs, so I decided to find a way to calculate and display the “Queen Bee” threshold automatically.

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Constructing Reality, or Breaking the Rules?

AI-powered photo editing tools built into some of the latest smartphones, including the newly released Google Pixel 8 series, give us the ever-increasing ability to showcase our own versions of reality. Photography, as an extension of portraiture, has always been a “constructed” medium, so what makes these features feel so problematic? Is it all a bit of an overreaction? Let’s explore!

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On the Merge of Something Awesome

I recently detailed a technique for auto-generating a slideshow in Adobe InDesign using data from a spreadsheet. (This is great for awards ceremonies!) But wouldn’t it be cool if there were a way to do this completely within the “free” Google ecosystem? By using a tool called Google Apps Script, I determined that you can, in fact, accomplish the same thing with Google Sheets and Google Slides.

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How to Generate an Awards Slideshow Using a Spreadsheet and InDesign

During the pandemic, virtual ceremonies often replaced in-person graduations, inductions, and other award ceremonies.

Creating a slideshow with awardees’ names and photos could add some visual interest, but depending on the size of the group, they could also take a long time to build.

In this tutorial, I walk readers through a method to automate this process using a spreadsheet and Adobe InDesign. The same techniques could also be used for any other resources, like certificates or photo directories, that require merging text and images from a list into a pre-made template.

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Rough Surf: Emulating MacOS 9 – in 2022!

After successfully booting MS-DOS inside an emulator on my M1-powered MacBook Pro, I decided to try out another ancient operating system: MacOS 9.

In this post, I explore what it takes to get it running and what it’s like to browse today’s World Wide Web using a 20-year-old operating system.

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How to Run MS-DOS on a Mac with Intel or M-series Processor

Let’s imagine for a moment that you’re feeling a bit fed up with the state of the world and are yearning for the good old days of the 1990s when, because you were a kid, you were oblivious to much of whatever might have been wrong with the world at that point in time.

Now, suppose the epitome of 90s-era technology for you is taking a trip to your dad’s office in the big city, where his corporate computer was just better enough than the crummy one at home that you could reliably use it to play a really cool new game—namely, SimCity 2000. And finally, suppose you’d like to fulfill your craving for nostalgia by playing that game, which was designed for MS-DOS (an OS created in the 80s) on your brand new MacBook Pro (which was released in 2021).

Well, there’s a problem. Actually, a few problems (not the least of which is that I have too much time on my hands).

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How to get answer choice stats from a Schoology assessment

For some reason, Schoology’s “Assessment” tool cannot tell you how many students picked an individual incorrect answer choice on a multiple choice question.

(This is particularly annoying because Schoology’s similar but older “Test/Quiz” tool CAN give you this information!)

Even though Schoology can’t summarize the results for you, the information is all there. We just need a way to process it.

In this tutorial, I walk readers through a method involving JavaScript that can be used to scrape the answer data from a Schoology page and retrieve the missing information.

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How to Split Excel Data into Multiple Columns Without Getting It All Jumbled Up

Suppose you’ve asked someone for some information. You were hoping for a nice, neat table, but what they’ve sent you back is, well, messy. Maybe the columns aren’t broken up the way you expected. Or maybe you don’t even have any columns, and it’s just several rows of information pasted into an email.

If you need to sort your data, run a mail merge, or do anything useful with this information, you’re going to have to clean it up first. Fortunately, Excel has a tool for just this type of problem: Text to Columns.

Let’s take a look at how to use that tool along with the Find/Replace feature to organize a stubborn set of data.

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