The score sees only what it counts.

INSTRUMENTS / VALUE & POWER

Constructed example

Spend the effort. Inspect the reward.

Change an input. Inspect every step. Keep a fixed record.

A working copy · changes stay here until you save

incentives-v1

01 / THE QUESTION

Is a closed case a solved problem?

You have twenty effort units and twenty cases. Resolving a case costs two units. Closing one administratively costs one. Which action does the score reward?

Keep a first thought

Optional. Included only when you explicitly save; excluded from shared links.

Constructed data · every relationship and outcome is supplied.

02 / OPEN THE MODEL

WHAT THE SCORE SEES

15closed cases

Changing the reward changes the score. Your case allocation stays fixed.

THE SAME TWENTY EFFORT UNITS

10 units resolve 5 cases. 10 units close 10 other cases administratively. R = resolution effort; C = administrative closure effort.

WHAT HAPPENED TO THE CASES

✓ Resolved (5) · × Administratively closed (10) · ○ Untouched (5). 15 cases remain unresolved.

C01 · Resolved: two effort units were assigned.

For the selected reward, this model’s highest score uses 0 resolutions. Changing the reward keeps your allocation unchanged.

15Closed casescases
5Confirmed resolutionscases
15Reward · closedclosed cases

Follow the idea.

A concept, in three frames

Read the score.

Check which outcomes the reward counts.

Follow the effort.

Resolution and closure use effort differently.

Inspect the cases.

A closed case can remain unresolved.

HOLD ONE VERSION STILL

What changes when you change the model?

Keep the current inputs beside your next adjustment.

Name the outcome before choosing the score.

Counting closures treats a resolution and an administrative closure alike. Counting confirmed resolutions recognizes a different outcome under the same effort budget. Here r means resolutions and c means administrative closures.

Read the investigation →
Save this experiment

Saved only in this browser. Clearing browser data removes local copies; export a copy from your notebook to keep it.

MODEL & LIMITS

What this model leaves open

This model supplies the action costs and assumes perfect confirmation of resolutions. It does not predict how real people behave or prove that every target fails.

  1. InputsWhat is supplied?
  2. DefinitionWhat is counted?
  3. InferenceWhat follows?
Inspect the exact workings

Effort: 2 × 5 + 10 = 20 units. Distinct acted-on cases: 5 + 10 = 15. Unresolved includes administrative closures and untouched cases: 10 + 5 = 15.

All eleven feasible allocations · every row spends twenty effort units
ResolutionsAdministrative closuresClosedUnresolvedSelected reward
020202020 closed cases
118191919 closed cases
216181818 closed cases
314171717 closed cases
412161616 closed cases
510151515 closed cases
68141414 closed cases
76131313 closed cases
84121212 closed cases
92111111 closed cases
100101010 closed cases

Case ledger: C01 resolved; C02 resolved; C03 resolved; C04 resolved; C05 resolved; C06 administrative; C07 administrative; C08 administrative; C09 administrative; C10 administrative; C11 administrative; C12 administrative; C13 administrative; C14 administrative; C15 administrative; C16 untouched; C17 untouched; C18 untouched; C19 untouched; C20 untouched.

Assumptions, sources and evidence status

Original constructed fixture: constructed-incentives-v1. incentives-v1. No empirical observations are represented by these example counts.

  • This is a deterministic constructed model, not an empirical claim about workers or inevitable target failure.
  • Confirmed resolutions are assumed to be perfectly observed; real verification can be difficult and costly.
  • Switching the reward does not reallocate effort. Closed and resolved counts overlap and must not be added.
Read the definition and primary background sources →