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MetaPoll | Docs
  • Introducing MetaPoll
  • Getting Started
    • Take the MetaPoll tour!
    • FAQs
    • Quickstart Mission
  • MetaPoll User Guide
    • Signing In
    • Adding and Removing DAOs
    • Browsing MetaPolls
      • Filtering MetaPolls by DAO
      • Search and Other Filters
      • Main card
    • Viewing MetaPoll Results
      • Snapshots
      • Options
      • Child Options, Layers, and Navigation
    • Voting
      • Ranked and Unranked Options
      • Ranking and Unranking Methods
      • Casting Your Vote
      • Viewing Vote History
    • Eligible Tokens and Vote Calculation
    • Vote Decay
    • Graduation
  • Authoring MetaPolls
    • Basics of Creating MetaPolls
      • Creating a new MetaPoll
      • Setting up the MetaPoll
      • Creating Options
      • Publishing a MetaPoll
      • Managing your MetaPolls
    • Working with MPTS format
    • Option space design
      • Option Naming Styles: The Abstraction-Precision Trade-off
      • State Change Loop
      • Utility Formats
    • Example MetaPoll types
      • 1. Control Surfaces for Automated Systems
      • 2. Information Sources for Decision-Making
      • 3. Proposal Temperature Checks
      • 4. Proposal Election and Expectation Management
      • 5. Representative Guidance Systems
  • Hypothetical MetaPolls
  • Advanced Topics
    • Decision Spaces
    • Snapshot Data Structure
    • VCIP - Voter Compute Integrity Proof
    • VDIP - Voter Data Integrity Proof
    • Arweave Perma Storage
    • Verkle Trees
    • ZKsnarks
  • Appendix
    • Links
    • Glossary
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  1. Authoring MetaPolls
  2. Example MetaPoll types

3. Proposal Temperature Checks

A hybrid approach uses MetaPolls to establish community alignment before formal proposals are submitted. This front-loads consensus-building, making the proposal process more efficient.

How It Works

Before creating a detailed proposal, community members use a MetaPoll to establish baseline preferences on key parameters. Future proposal authors can then craft their submissions to align with these established preferences, increasing the likelihood of approval.

Effective proposal temperature checks:

  • Explore the full parameter space for upcoming decisions

  • Focus on outcomes rather than implementation details

  • Provide sufficient specificity to guide proposal development

  • Remain active over time to reveal preference shifts

For example, before soliciting event planning proposals, a community might use this MetaPoll:

title [desired community event proposal]

options [

=Location

==North America

===USA

====NYC

====Denver

...

=Format

==Mixer/Networking

==Dance Party

...

=Event size (people)

==10

==20

...

]

(Full example abbreviated for space but includes extensive options across multiple dimensions)

This approach transforms the proposal process from guesswork ("what does the community want?") to execution excellence ("who can best deliver what the community already knows it wants?"). It shifts the competitive landscape for proposal authors from creative speculation to implementation quality.

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Last updated 10 days ago