ds-vote

name	ds-vote
description	Use when checking answer stability — runs the same solver N times and returns the majority answer + agreement rate

ds-vote : run the same solver N times and count votes

When this applies

Use ds-vote when you want a fast stability check on a moderately important question. You want to know: if I run this again, would I get the same answer?

Do NOT use when:

• The stakes are high and you need independent confirmation — use ds-spike (different personas, potential debate round).
• You already have multiple candidate answers in hand — use ds-reconcile.

The cardinal rule

This is NOT an ensemble. Solvers use the same model and persona across all N runs, so agreement indicates stability, not independent confirmation. Consistent agreement means the answer is stable; disagreement means the question is sensitive to code or interpretation choices. For true independence (diversity of approach), use ds-spike.

Based on self-consistency sampling: Wang et al. 2022 (arXiv:2203.11171).

How to run it

1. Run ds-star-plus N times (default N=3) with varied random seeds but identical model and persona settings.
2. Collect the result of each run as a record:

   {"id": f"vote-{i}", "answer": answer_i, "sufficient": sufficient_i}
   

3. Call aggregate() from ../ds-spike/scripts/aggregate.py on all N records.
4. Report the majority answer + confidence (fraction of runs agreeing) + any minority answers.

Output

• Majority answer — the answer returned by the plurality of runs (weighted by sufficiency)
• Confidence — fraction of total weight behind the majority answer (0.0–1.0)
• Minority answers — any answers returned by fewer runs (surface these; they indicate instability)

Example:

Majority answer: 41.7   confidence: 0.83   (2/3 runs)
Minority answer: 39.1   (1 run — different handling of NaN rows)

Quick reference

from aggregate import aggregate   # ../ds-spike/scripts/aggregate.py

records = [
    {"id": "vote-1", "answer": answer_1, "sufficient": sufficient_1},
    {"id": "vote-2", "answer": answer_2, "sufficient": sufficient_2},
    {"id": "vote-3", "answer": answer_3, "sufficient": sufficient_3},
]
result = aggregate(records)
print("majority:", result["answer"], "confidence:", result["confidence"])

• Default N = 3 (add runs for higher confidence at higher cost)
• Same model and persona across all runs (only seed varies)
• aggregate() for majority vote and confidence: ../ds-spike/scripts/aggregate.py
• Reference: Wang et al. 2022, arXiv:2203.11171 ("Self-Consistency Improves Chain of Thought Reasoning in Language Models")