In October 2021, we published an article interrogating trichotomy, debate lingo for the classic tripartite categorization of resolutions as fact, value, or policy. Before you continue reading, make sure you revisit the original piece—this analysis depends on terminology and concepts introduced there! The initial article sparked some lively conversation, so I’ll be addressing some of the responses in this sequel.
What’s the Point?
Danielle Miller poses an excellent question: Why bother?
“…do you think we even should nitpick this deeply? I think it’s perfectly possible that there are no perfect resolution definitions, and we just have to use our judgment for individual rounds using the categories as guidelines, and focus trichromatic arguments on the impact to the round.”
While it’s certainly possible that establishing pristine parameters is unattainable, this further underscores the necessity of rigorous conceptual analysis. Suppose you’re in a parli round, faced with a seemingly unclassifiable resolution. Remember that correct categorization matters a ton—if you interpret the round as a value resolution and your judge buys your opponents’ policy, they’ll penalize you for not proposing a plan. Grappling with the underlying theory enables you to navigate nebulous categorizations incisively—the more you’ve contemplated the differences between fact, value, and policy, the better you’ll engage tricky topics.
Moreover, this pursuit combats bad theory. For instance, many collegiate debaters invoke “preponderance of evidence” as the incontrovertible standard for fact resolutions, but my categorization scheme highlights problems with this convention, ultimately promoting cleaner debate rounds.
Pragmatic reasons aside, this exploration is also inherently enjoyable (most of the time—that is, if you haven’t procrastinated on your blog post…)
Since the original article primarily discussed fact and value topics, Danielle also asked about policy resolutions:
“I would appreciate it if you could go into more detail on the line between policy and fact. If you would consider, for example, ‘things the US government should do’ as a predicate category, then policy resolutions would fit under your fact resolution definition..”
Predicate categories aren’t limited to fact resolutions, however. On the contrary, they’re an intrinsic feature of all propositions irrespective of their categorization—everything from “Socrates is mortal” to “the United States federal government should significantly reform its policies regarding convicted prisoners under federal jurisdiction” contains a subject and a predicate. Therefore, just because traditional policy resolutions have predicate categories doesn’t mean they’re incognito fact resolutions.
As Danielle correctly identifies, policy predicate categories assume the general form of “things [X actor] should do.” Applied to the 2021-22 NCFCA and Stoa resolutions, this looks like:
|The United States federal government should significantly reform its policies regarding convicted prisoners under federal jurisdiction.
|Reforming policies regarding convicted prisoners under federal jurisdiction
|Action the USFG should take
|The United States federal government should substantially reform the use of artificial intelligence technology.
|Reforming the use of AI technology
|Action the USFG should take
|The United States federal government should outlaw torture.
|Action the USFG should take
Weighing Mechanisms and Case Structure
This system accommodates traditional policy debate burdens and case structure. Why? Proving that the subject belongs in the predicate category requires debaters to articulate some standard or weighing mechanism for the predicate category, like net benefits, which triggers conventional TP burdens like proving stock issues and specifying a particular plan. Think about it this way:
- To determine whether AI tech reform is an action the USFG should take (placing the subject in the predicate category), you must provide a standard or weighing mechanism for the predicate category. You propose the standard of net benefits, which means that if an AI tech reform does more good than harm, the USFG should take the action.
- To prove that AI tech reform is net beneficial, you must (1) specify the reform you’re talking about (which requires some kind of plan text, likely with agency, enforcement, etc.) and (2) compare your reform with the status quo (which probably entails some kind of harms/advantages calculus, outweighing disadvantages, demonstrating solvency, etc.)
Don’t view this as fundamentally discordant with policy burdens—classic TP case structure and negative strategies emanate from this paradigm.
Furthermore, this categorization scheme encompasses “unconventional” weighing mechanisms for policy debate. Take the torture example above, for instance. Instead of running net benefits, you could alternatively pitch a deontological moral framework—arguing governments have a moral obligation to prohibit torture. That provides a reason outside the typical NB framework for situating the subject in the predicate category.
Differentiating Policy from Fact/Value
But wait… how does that interact with the distinction between value and policy? If the difference between fact and value resolutions (as explicated in the previous article) is value resolutions traffic in value judgments whereas fact resolutions don’t, aren’t policy resolutions—from the more obvious case of torture to the less obvious case of AI—also engaging in value judgments? Doesn’t that collapse the distinction?
On the contrary, policy resolutions reflect a certain kind of value judgment—one that suggests action. Thus, you can label a resolution using the following matrix:
- Does the resolution make a value judgment?
- If not, it’s a fact resolution.
- If so, it’s a value or policy resolution.
- If the resolution makes a value judgment, does it suggest action?
- If not, it’s a value resolution.
- If so, it’s a policy resolution.
In other words, policy resolutions are a specific subset of value judgments. Since they require a series of unique burdens compared to their value resolution siblings, they warrant separate categorization.
Jadon’s Alternate Approach to Fact/Value
On a totally divergent note to the above, I figured I’d summarize Ethos CEO Jadon Buzzard’s approach to fact/value resolutions—we’ve both arrived at internally consistent versions of crystalizing the dichotomy. This is just a (hopefully tantalizing) snapshot—we’re hoping to collaborate on a blog post in the future ironing out more details.
- Fact resolutions don’t make a value judgment. They can be either descriptive (“Resolved: Hot dogs are sandwiches”) or comparative (“Resolved: Hybrid vehicles have better fuel economy than minivans”).
- Value resolutions make a value judgment. They can be either descriptive (“Resolved: Preventive war is ethical”) or comparative (“Resolved: Privacy is more important than security”.)
- Fact resolutions are descriptive. They can either make a value judgment (“Resolved: Preventive war is ethical”) or not make a value judgment (“Resolved: Hot dogs are sandwiches”).
- Value resolutions are comparative. They can either make a value judgment (“Resolved: Privacy is more important than security”) or not make a value judgment (“Resolved: Hybrid vehicles have better fuel economy than minivans”).
At some point, we’ll further explore the merits and drawbacks of these interpretations, but for now, I figured I’d qualify my previous article by inserting this alternate perspective.
Hope y’all found this sequel helpful. I look forward to engaging with your feedback!
Joel Erickson coaches Lincoln-Douglas debate for Ethos and British parliamentary debate at Wheaton College, where he studied philosophy.