Every score tells
a real story.
K Cha Sarkar? turns 1-to-5 ratings into a live, weighted public score. Here is exactly how — no black box, no mystery.
From citizen to score
What happens after you press Submit?
You rate
Stars + optional office visit + optional comment.
Spam check
4 automatic rules filter obvious manipulation.
Trust weight
Score is weighted 0.5× to 1.0× by context.
Score computed
Weighted average across all valid responses.
Public score
Area and office scores update live.
Two-track rating system
Every rating feeds two scores at once.
When you visit a specific government office and rate it, your data flows into two separate scoring tracks simultaneously.
Area score
Always updated
Your 6 area-level ratings (roads, offices, civic, traffic, safety, hope) always contribute to the ward or municipality score.
Office score
Only when you select a specific office
When you pick a specific office, 3 extra star ratings plus your bribe report feed the office's own score — separate from the area.
Office overall = average of all 4 factors including integrity (0 if bribe reported, 100 if clean).
Area and office are never confused.
If you rate a hospital in Kathmandu, the hospital gets its own score and the ward where it sits also gets your 6 area ratings. A bad hospital does not automatically make the whole ward score drop — each track is separate.
Score formula
Stars become numbers. Numbers become scores.
Very bad
0
out of 100
Bad
25
out of 100
Okay
50
out of 100
Good
75
out of 100
Excellent
100
out of 100
(r − 1) × 25
where r = star rating (1–5)
Try it yourself
Click the stars to see how scores change in real time
Weighted area score
= roads×20% + office×20% + safety×20% + civic×15% + hope×15% + traffic×10%
Trust system
Not every vote counts the same — and that is by design.
More context = more trust. Someone who visited an office and provided details is harder to fake than a click with no context.
Anonymous
Area rating only, no office visited.
Anonymous + context
Rated an area and also visited a government office.
Verified (coming soon)
Phone or ID verified account. Highest trust.
Suspicious or flagged ratings
Weight 0 — they are excluded from all score calculations until a moderator reviews and approves them. Flagging never deletes data, it just pauses its contribution.
Score bands
Four bands. Four stories.
Citizens are satisfied. Services work.
Mostly positive with room to improve.
Serious concerns reported by citizens.
Widespread frustration. Needs urgent attention.
Confidence labels
How many ratings does a score need to be reliable?
A score from 2 people means something very different than a score from 200. Confidence labels tell you exactly where each area sits.
Insufficient
0–4
Visible privately, not in public rankings.
Low
5–19
Shown publicly but treat with caution.
Medium
20–49
A reasonable signal of area sentiment.
High
50+
50+ ratings and at least 30% verified.
Anti-spam
Four rules that keep the scores honest.
We run automatic checks on every submission. Flagged ratings are paused — not deleted — until a moderator reviews them.
One per 30 days
Same browser can only rate the same area once every 30 days.
IP rate limit
More than 5 submissions from one IP in an hour triggers automatic review.
Duplicate detection
Identical comments submitted multiple times are caught and flagged.
All-extremes filter
All 1s or all 5s with no comment or context gets flagged for review.
House of Representatives scores
Every MP gets the score for the people they represent.
Nepal's 275 HoR members are scored differently based on how they were elected — direct or proportional representation.
Direct (165 members)
Constituency scoreDirect members represent a specific constituency. Their score is the weighted average of all citizen ratings from wards and municipalities inside their own constituency boundary — not the whole district.
Proportional (110 members)
District scorePR members represent the entire district they are listed under. Their score is the weighted average of all citizen ratings from every area in that district.
Limitations
What this data is — and what it is not.
Citizen perception
Scores reflect how citizens feel. That feeling matters — but it is not the same as an official audit or measurement.
Self-selected respondents
People who choose to rate are not a random sample. More engaged citizens — especially frustrated ones — are more likely to respond.
Low-data areas are less reliable
An area with 3 ratings can swing wildly from one new submission. Use confidence labels as your guide.
Snapshots, not ground truth
Scores change as new ratings come in. A good score today does not lock in future performance.
Ready to add your voice to the score?
It takes 30 seconds.