Editorial
How we decide what gets surfaced
Event Dime uses structured event data, source signals, and recommendation logic to decide what to show. The goal is to expose enough context for users and admins to understand why a page exists, why a listing appears, and how the recommendation score was produced.
Recommendation principles
- Preference aware
Recommendations are based on saved category preferences and user activity.
- Explainable
Admin views expose score, source, calculation basis, and detailed reasoning when available.
- Live when possible
The admin page runs the live scorer so you can compare the current output with the stored record.
- Fallback safe
If the LLM path cannot run, the system falls back to the heuristic scorer.
Content quality rules
- Use original copy
City and trust pages include original explanatory text instead of repeating only source data.
- Avoid thin pages
Private utility pages can be noindexed so search engines focus on meaningful public content.
- Keep sources visible
Readers should be able to tell where a listing came from and when it was generated.
- Correct mistakes quickly
When a listing is wrong, the contact path should make correction easy.