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Robin Hood index instrument

DefinitionThe fraction of a total count that would have to move from points above the mean to points below it to make every count equal. Equation 0.35. Also Robin Hood.
ExampleIf 20 percent of the rows take 60 percent of the retrievals, the Robin Hood index is 0.40.
BookData Mining as Observation, draft 0.2, commit f3914f0; entry id robin-hood-index, kind instrument.
Statusno ledger row names this entry. Corrections: none recorded.
Defining equation

Book equation 0.35.

Assumptions and scope
  • The fraction of the total count that would have to move from points above the mean to points below it to make every count equal, the excess above the mean over the total, which is half the total absolute deviation over the total. It is nonnegative, zero exactly at equality, at most one, and unchanged by a common scaling of the counts.
  • The strata design reports it per area beside the skew, and the first run’s ratio of 1.30 against a bar of 1.5 is the number the abstention rule was written around.
Prior artnone recorded
Evidencelean/DataMiningAsObservation/RobinHood.lean
Reviewednot yet reviewed; generated 2026-09-10 from records at the commits on the provenance page.
00.5100.51share of rowsshare of retrievalsequal shares is the diagonalthe index is the largest vertical gap
The share of retrievals that would have to move to equalize the rows.

Equation

Book equation 0.35.

\[\mathrm{RH}=\sum_i\max\!\Big(0,\ \frac{N_i}{\sum_j N_j}-\frac1n\Big).\]

Conditions

Conditions are curated in entries.toml rather than read from a record.

Ledger

none

First stated

Hoover’s index of concentration, applied to neighbour counts in turboquant-pro’s strata design, turboquant-pro/docs/STRATA_RFC.md:24-98, and chapter 0 section 0.16 of Data Mining as Observation.

Measurements

none

Failures and corrections

none

Invariance envelope

none declared

Machine checked

lean/DataMiningAsObservation/RobinHood.lean, theorems sum_dev, excess_eq_half_abs, robinHood_nonneg, robinHood_eq_zero_iff, robinHood_le_one, robinHood_scale, at observation-data-mining f3914f0; what the check covers is stated in the book’s appendix C.

Used in

Data Mining as Observation chapters 0, 10.

Related

hubness; anti-hub; Poisson ceiling; abstention.

See also

Book equations stated beside the entry’s terms, not defining it: 10.4.

Ledger rows that cite the entry’s records without naming it: NEG-14.

Sources-table rows that share a record with the entry without naming it: chapter 10 section 10.4.

Status

Generated 2026-09-10 by encyclopedia/generate.py; book at observation-data-mining f3914f0; the commit of every record is listed in the encyclopedia’s provenance.

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