Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in [1].
Proportional Public Decisions
Authors: Piotr Skowron, Adrian Górecki5191-5198
AAAI 2022 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We formulate new criteria of proportionality and analyse two rules, Proportional Approval Voting and the Metod of Equal Shares, inspired by the corresponding committee election rules. We prove that the two rules provide very strong proportionality guarantees when applied to the setting of public decisions. |
| Researcher Affiliation | Academia | Piotr Skowron, Adrian G orecki University of Warsaw EMAIL, EMAIL |
| Pseudocode | No | The paper describes rules (PAV, MES, Me Cor A) in textual format but does not provide structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide concrete access to source code for the methodology described in this paper. |
| Open Datasets | No | The paper is theoretical and does not utilize datasets for empirical evaluation. |
| Dataset Splits | No | The paper is theoretical and does not utilize datasets, therefore no dataset split information is provided. |
| Hardware Specification | No | The paper is theoretical and does not describe experiments that would require hardware specifications. |
| Software Dependencies | No | The paper is theoretical and does not describe experiments that would require software dependencies with version numbers. |
| Experiment Setup | No | The paper is theoretical and does not describe an experimental setup with hyperparameters or training configurations. |