Models

And their structural failures

The two framework impacts articulated most often in debate are clash and fairness. Clash operates in a model-based framework: if we debated under a single interpretation, which would produce better education? While fairness can operate under this same models-based approach, it’s more often articulated as in-round offense: something unfair was done in this round, and only the ballot can remedy it.

A relatively recent phenomenon in critical debate involves going for arguments about it being impossible to actualize a model of debate. Regardless of how a judge votes in a single debate round, it is impossible for them to actually enforce or guarantee that critical affirmatives are not read in the future. Even a hundred rounds would barely shift the needle. 

Critical teams are correct about this. Models of debate cannot exist. Judges can only affect what goes on in the particular round they are judging. 

Ambiguity

What is a model? Even though the term is thrown around in many debates, it lacks a clear definition that describes it. Here are a few, representing a “model” where affirmatives must be topical:

Type one:

Judges universally vote against untopical affirmatives, but they can be read.

Type two:

No untopical affirmative is read, and teams somehow know that they cannot read untopical affirmatives. 

Type three:

No untopical affirmative is read, and teams don’t know that they cannot read untopical affirmatives, but are somehow “fiated” to read untopical affirmatives even though they don’t know if they are forced to. 

I’ll reference type one/two/three models throughout this article.

Failures of Type One

“Type one” models (where judges universally vote against untopical affirmatives) cannot solve the clash impact to framework. The impact is solely about whether the arguments read in debate are refutable. If a “model” for debate allows teams to read critical affirmatives at all, then it cannot access the clash impact.

These types of models also mitigate the framework team’s predictability impact in the long run. In the world of the counter-interpretation (still a type-one model, where judges vote against teams that do not read an affirmative that fits within the counter-interpretation), policy teams would suddenly start losing every debate. Eventually, they would realize that they must read counterinterp-adjacent affirmatives in order to win, which would eventually result in debate being exclusively over the counter-interpretation.

As follows, it seems unstrategic for teams going for framework to explain models of debate like this. 

Failures of Type Two

“Type two” models clearly mitigate the predictability impact. Teams know (maybe by NSDA decree, tournament rules, or something similar) that they must read an untopical affirmative. That makes the reading of critical affirmatives predictable for both teams, because they know that every team at the tournament must be reading one.

Failures of Type Three

“Type three” models are strange and difficult to explain. They almost feel like an abuse of fiat, creating a model in which teams universally agree to an interpretation without knowing that they have. It’s akin to “mindset fiat” or “object fiat” as described in other debates. 

However, this seems like the only way for the framework team to access the full scope of the predictability impact. Under the counter-interpretation, teams would be just as surprised to see a critical affirmative as they are under the “affirmatives must be topical” interpretation, even though every single team would read a critical affirmative.

There are also clear disadvantages to thinking about debate in this manner. It could never be actualized, warps reality, and feels as though it has been exclusively manufactured to preserve the impact to predictability. 

Policy vs. Policy Debates

Models also apply in policy vs. policy debates. Nearly every theory, competition, or topicality debate operates within a models-based framework. Contrasting critical debates, policy teams barely bring up these issues with models, and instead just agree that teams get access to models-based clash and education impacts. 

There is also usually little discussion of what a model should include, either leaving a judge making guesses or simply overlooking this seemingly very relevant issue.