Hey, everyone, welcome to the eighth installment of the Inside Java series, also known as

Session 162 of the Behaviorable Observations podcast. And in this episode, Dr.'s Linda LeBlanc,

Claire St. Peter, and Jeff Tiger, join me to discuss a paper, Jeff co-wrote with Hannah Efforts.

It's called On the Validity of Data Produced by Isolated and Synthesized Contingencies

during the Functional Analysis of Problem Behavior.

And you can find this paper in the latest issue of Java.

In this paper, Jeff and Hannah introduced the concepts of sensitivity, specificity,

discriminant validity, and predictability.

And they discuss why these are important.

Then they analyzed both the, what's called the, what they're calling the isolated contingency

analysis, better known as the standard functional analysis, and synthesized

functional analysis, aka the ISCA or practical functional assessment, through these lenses.

As you might imagine, we spent the episode discussing all aspects of this paper, including

the author's motivation to write it, what they learned, and what implications

stem from their findings for students and practitioners.

We mentioned a few different references in today's show, and you can find those at the show

notes over at behavioral observations.com, including the slide that Jeff mentioned,

as well as a link to the Max Powers episode of The Simpsons that he also referenced.

As with other Inside Job series podcast, this is a commercial free episode.

However, these Inside Series shows are available to purchase as CEOs.

There are discounts available for multiple event purchases if you need more than one CEO.

And there are discounts available for those who join the Behavioral Observations Patreon Group.

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