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Category
First title

Pragmata

2026

Category
Second title

We Are OFK

2022

Pragmata vs We Are OFK: Which Is More Woke?

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We Are OFK appears more woke than Pragmata based on AI analysis, with a difference of about 53 points. Community votes are split or too thin to call a clear winner yet.

GamePragmata2026
10Score
Peak Gaming

Community (votes): ~54/100

See full breakdown for Pragmata
GameWe Are OFK2022
63Score
Very Woke

Community (votes): not enough data yet

See full breakdown for We Are OFK

AI vs community

AI verdict

We Are OFK is more woke than Pragmata (AI).

We Are OFK leads by 53 points on the AI scale.

Community verdict

Community averages are too close to call (or one side has no votes yet).

Why the scores diverge

  • The 53-point gap reflects how much ideology steers each story on our six-dimension pass, not just vibes.
  • We Are OFK highlight: Dialogue is often laden with social messaging and modern cultural references.
  • Pragmata highlight: Dialogue serves the narrative without heavy-handed messaging.
  • Pragmata: Characters are primarily defined by their roles in the story rather than as symbols.
  • We Are OFK: Characters feel crafted more for representation than for depth or growth.

We Are OFK reads higher on message-first dialogue than Pragmata, which nudges the overall profile message-forward. We Are OFK reads higher on ideology over story than Pragmata, which nudges the overall profile message-forward. We Are OFK reads higher on cultural normalization framing than Pragmata, which nudges the overall profile message-forward.

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Frequently asked questions

Which is more woke, Pragmata or We Are OFK?
We Are OFK scores higher on the AI pass (63/100 vs 10/100).
What do community votes say?
Community averages are within the tie band or too close to call (54 vs n/a on our vote-weighted scale).
Why might AI and votes disagree?
AI scores come from a structured model pass; votes capture how people read the politics or messaging. Trailers, culture-war framing, and release timing can push votes away from the model.