Model Scorecard: What Counts as an Explanation?
A model is not just an answer that feels satisfying. A model earns trust by making predictions, surviving checks, and explaining many observations with the same rules.
The Scorecard
| Criterion | Strong model | Weak model |
|---|---|---|
| Prediction | States what should happen before looking. | Explains only after the result is known. |
| Precision | Uses numbers, locations, dates, and tolerances. | Uses vague words like “perspective,” “energy,” or “deception” without calculation. |
| Scope | Explains related evidence with the same geometry. | Needs a different exception for every topic. |
| Risk | Could be proven wrong by a clear observation. | Cannot name any possible falsifier. |
| Independence | Can be checked by ordinary observers and independent sources. | Depends on dismissing every conflicting observer as fooled or corrupt. |
Apply It to Flat-Earth Claims
When someone offers a flat-earth explanation, score it. Does it predict sunrise direction, route distances, southern stars, eclipse timing, tides, and horizon behavior together? Or does it only answer the one meme currently on screen?
One Useful Question
What would this model predict if we changed the location, date, or direction? A real model can travel. A fragile claim only works in its original meme.