Exercise 15b — a 0–5 score profile (which method is this?)¶

Generated from ex15_score_profile.yaml — do not edit by hand. Regenerate: python STARVote_LH_tabulation_engine/tools_adam/scripts/build_yaml_pages.py.

Method: STAR (single winner) · 1 seat · Expected winner: Clara

▶ Live on BetterVoting: vote · results ↗ (election tfm64p · test BV2259).

Scenario¶

Part (b) of Exercise 15 — "Read the ballot, name the method."

Four voters rate four candidates 0-5, each candidate judged on its own scale with no ordering required. That is a CARDINAL ballot, and adding the columns is SCORE VOTING (aka Range): Clara 19, Diego 13, Bruno 11, Alice 7. Clara wins.

The file runs as STAR because the teaching CLI has no first-class voting_method: Score — and that turns out to be the useful part. STAR's Scoring Round IS the score-voting tally, so the totals printed below are the Score result; the runoff is the extra step Score doesn't take. Here it changes nothing: Clara also wins the runoff 4-0, is the Condorcet winner, and the engine prints no [Divergence from STAR] block at all because every method agrees.

Kept deliberately: an election where nothing diverges is a fair baseline for a library full of elections that do. Clara is scored top or joint-top by all four voters, so there is no question for a method to disagree about.

A textbook-style prompt, rebuilt with named candidates so the rows line up A/B/C/D -> Alice/Bruno/Clara/Diego. Part (a) is ex15_approval_yes_no.yaml.

Exercise page: ../ex15_read_the_ballot.md Live results: https://bettervoting.com/tfm64p/results (BV2259 — BetterVoting's own STAR count agrees: Clara.)

Ballots¶

Row 1 = candidate names; each later row is one voter's 0–5 scores (a N × prefix = N identical ballots).

Alice,Bruno,Clara,Diego
0,2,5,4   # voter 1
3,5,5,3   # voter 2
0,1,5,4   # voter 3
4,3,4,2   # voter 4

What the engine says¶

The count, step by step — the rounds and how the winner is reached:

--- STAR Voting Method (single winner) ---

[STAR Voting]
 Tabulating 4 ballots.
Alice,Bruno,Clara,Diego
    0,    2,    5,    4
    3,    5,    5,    3
    0,    1,    5,    4
    4,    3,    4,    2

[STAR Voting: Scoring Round]
 The two highest-scoring candidates advance to the next round.
   Clara         -- 19 -- First place
   Diego         -- 13 -- Second place
   Bruno         -- 11
   Alice         --  7
 Clara and Diego advance.

[STAR Voting: Automatic Runoff Round]
 The candidate preferred in the most head-to-head matchups wins.
   Clara         -- 4 -- First place
   Diego         -- 0
   Equal Support -- 0
 Clara wins.
   Runoff math:
     4  ballots cast
   − 0  Equal Support (no preference between the two finalists)
     ─
     4  voters with a preference  (majority = 3)
           Clara 4 (100%)  ·  Diego 0 (0%)

[STAR Voting: Winner — STAR Voting Method (single winner)]
 Clara

Full audit — preference matrix, Condorcet, and score distribution¶

--- Runoff (Preference) Matrix ---
Head-to-head / pairwise comparison
Legend: For - Equal Support - Against
        * indicates Top 2 Finalist
               |    Alice   |   Bruno   | * Clara   | * Diego   |
-----------------------------------------------------------------
       Alice > |    ---     |1 - 0 - 3  |0 - 1 - 3  |1 - 1 - 2  |
       Bruno > | 3 - 0 - 1  |   ---     |0 - 1 - 3  |2 - 0 - 2  |
     * Clara > | 3 - 1 - 0  |3 - 1 - 0  |   ---     |4 - 0 - 0  |
     * Diego > | 2 - 1 - 1  |2 - 0 - 2  |0 - 0 - 4  |   ---     |

[Condorcet Winner]
  Condorcet Winner: Clara — matches the STAR winner

[Condorcet Loser]
  Condorcet Loser: Alice — loses every head-to-head matchup

[Score Distribution] (how many ballots gave each star rating)
                Score
Candidate  5  4  3  2  1  0  | Total   Avg
Alice      0  1  1  0  0  2  |     7   1.8
Bruno      1  0  1  1  1  0  |    11   2.8
Clara      3  1  0  0  0  0  |    19   4.8
Diego      0  2  1  1  0  0  |    13   3.3

Everything in one file: the _tabulated mirror (regenerated on every run; every analysis forced on).

Run it yourself:

python STARVote_LH_tabulation_engine/starvote_larry_hastings.py 01_STAR/05_Practice/cases/ex15_score_profile.yaml

Exercise 15b — a 0–5 score profile (which method is this?)¶

Scenario¶

Ballots¶

What the engine says¶

Full audit — preference matrix, Condorcet, and score distribution¶

See also¶