Fairness in Long-Term Participatory Budgeting
Authors: Martin Lackner, Jan Maly, Simon Rey
IJCAI 2021 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | This paper presents a first formal framework for long-term PB, based on a sequence of budgeting problems as main input. We introduce a theory of fairness for this setting, focusing on three main concepts that apply to types (groups) of voters: (i) achieving equal welfare for all types, (ii) minimizing inequality of welfare (as measured by the Gini coefficient), and (iii) achieving equal welfare in the long run. For different notions of welfare, we investigate under which conditions these criteria can be satisfied, and analyze the computational complexity of verifying whether they hold. |
| Researcher Affiliation | Academia | DBAI, TU Wien, Vienna 2Institute for Logic, Language and Computation, University of Amsterdam, Amsterdam |
| Pseudocode | No | The paper does not contain structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide concrete access to source code for the methodology described. |
| Open Datasets | No | The paper does not describe the use of any dataset for training or evaluation, as it is a theoretical work. |
| Dataset Splits | No | The paper does not discuss dataset splits (training, validation, test) as it is a theoretical work. |
| Hardware Specification | No | The paper is theoretical and does not report on experiments, thus no hardware specifications are provided. |
| Software Dependencies | No | The paper is theoretical and does not report on experiments, thus no software dependencies are specified with version numbers. |
| Experiment Setup | No | The paper is theoretical and does not report on experiments, thus no specific experimental setup details like hyperparameters or training configurations are provided. |