Participation and Representation in Local Government Speech
- URL: http://arxiv.org/abs/2604.21202v1
- Date: Thu, 23 Apr 2026 01:47:56 GMT
- Title: Participation and Representation in Local Government Speech
- Abstract summary: We collect and transcribe a massive new dataset of city council meetings from 115 California cities over the last decade.<n>Public participants are substantially older, whiter, more male, more liberal, and more likely to own homes than the registered voter population.<n>We show that eliminating remote options reduces the number of speakers, but does not clearly change the composition of speakers.
- Score: 1.1458853556386799
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Local government meetings are the most common formal channel through which residents speak directly with elected officials, contest policies, and shape local agendas. However, data constraints typically limit the empirical study of these meetings to agendas, single cities, or short time horizons. We collect and transcribe a massive new dataset of city council meetings from 115 California cities over the last decade, using advanced transcription and diarization techniques to analyze the speech content of the meetings themselves. We document two sets of descriptive findings: First, city council meetings are frequent, long, and vary modestly across towns and time in topical content. Second, public participants are substantially older, whiter, more male, more liberal, and more likely to own homes than the registered voter population, and public participation surges when topics related to land use and zoning are included in meeting agendas. Given this skew, we examine the main policy lever municipalities have to shift participation patterns: meeting access costs. Exploiting pandemic-era variation in remote access, we show that eliminating remote options reduces the number of speakers, but does not clearly change the composition of speakers. Collectively, these results provide the most comprehensive empirical portrait to date of who participates in local democracy, what draws them in, and how institutional design choices shape both the volume and composition of public input.
Related papers
- Longitudinal Relational Publics and their Discursive Overlap with Issue Publics [2.406283079600984]
We show how a relational, audience-aware construct can reveal where and through whom political talk enters everyday online life.<n>In a case study, we identify 150 longitudinal publics from the following ties of a panel of Twitter/X users matched to U.S. voter records.<n>We find that the spaces that best fit the idea of a third space have the most politically heterogeneous audiences.
arXiv Detail & Related papers (2026-08-19T01:31:04Z) - From Speech to Interaction: Analyzing Multimodal Systems in Cocktail-Party Scenarios [68.14493981116665]
Humans have the remarkable ability to selectively attend to individual speakers while filtering out competing speech from nearby conversations.<n>This "cocktail party" scenario still presents severe challenges to speech recognition systems.<n>The CHiME-9 MCoRec task provides a testbed where systems must recognize groups of speakers and transcribe each of their conversations from audio-visual input.
arXiv Detail & Related papers (2026-08-09T06:11:38Z) - Mapping the Political Discourse in the Brazilian Chamber of Deputies: A Multi-Faceted Computational Approach [0.18567307896771823]
We introduce a scalable and generalizable computational framework that combines diachronic stylometric analysis, contextual topic modeling, and semantic clustering of deputies' speeches.<n>We apply this framework to a large-scale case study of the Brazilian Chamber of Deputies, using a corpus of over 450,000 speeches from 2003 to 2025.<n>Our results show a long-term stylistic shift toward shorter and more direct speeches, a legislative agenda that reorients sharply in response to national crises, and a granular map of discursive alignments.
arXiv Detail & Related papers (2026-04-23T17:46:33Z) - CitiLink-Minutes: A Multilayer Annotated Dataset of Municipal Meeting Minutes [4.992710184213374]
CitiLink-Minutes is an annotated dataset of 120 European Portuguese municipal meeting minutes from six municipalities.<n>The dataset contains over one million tokens, with all personal identifiers de-identified.
arXiv Detail & Related papers (2026-02-12T16:22:55Z) - MINGLE: VLMs for Semantically Complex Region Detection in Urban Scenes [49.89767522399176]
Group-level social interactions in public spaces are crucial for urban planning.<n>We introduce a social group region detection task, which requires inferring and spatially grounding visual regions defined by interpersonal relations.<n>We propose MINGLE, a modular three-stage pipeline that integrates human detection and depth estimation, VLM-based reasoning to classify pairwise social affiliation, and a lightweight spatial aggregation algorithm to localize socially connected groups.<n>We present a new dataset of 100K urban street-view images annotated with bounding boxes and labels for both individuals and socially interacting groups.
arXiv Detail & Related papers (2025-09-16T19:31:40Z) - What does the public want their local government to hear? A data-driven case study of public comments across the state of Michigan [4.695090078528572]
We propose a framework that characterizes comments along two dimensions: the local concerns where concerns are situated and the societal concerns raised.<n>Based on a large record of public comments we collect from 15 cities in Michigan.<n>We then demonstrate how our framework allows us to examine the salient local concerns and societal concerns that arise in our data.
arXiv Detail & Related papers (2025-07-24T14:10:04Z) - PUBLICSPEAK: Hearing the Public with a Probabilistic Framework in Local Government [0.01499944454332829]
We propose PUBLICSPEAK, a probabilistic framework which can discover public remarks in local government meetings.<n>We evaluate our approach on a novel dataset of local government meetings and find that PUBLICSPEAK improves over state-of-the-art by 10% on average, and by up to 40%.
arXiv Detail & Related papers (2025-03-14T17:04:36Z) - Representation Bias in Political Sample Simulations with Large Language Models [54.48283690603358]
This study seeks to identify and quantify biases in simulating political samples with Large Language Models.
Using the GPT-3.5-Turbo model, we leverage data from the American National Election Studies, German Longitudinal Election Study, Zuobiao dataset, and China Family Panel Studies.
arXiv Detail & Related papers (2024-07-16T05:52:26Z) - MeetingBank: A Benchmark Dataset for Meeting Summarization [37.761684754365945]
In this paper, we present MeetingBank, a new benchmark dataset of city council meetings over the past decade.
We make the collection, including meeting video links, transcripts, reference summaries, agenda, and other metadata, publicly available to facilitate the development of better meeting summarization techniques.
arXiv Detail & Related papers (2023-05-27T17:09:25Z) - Joint speaker diarisation and tracking in switching state-space model [51.58295550366401]
This paper proposes to explicitly track the movements of speakers while jointly performing diarisation within a unified model.
A state-space model is proposed, where the hidden state expresses the identity of the current active speaker and the predicted locations of all speakers.
Experiments on a Microsoft rich meeting transcription task show that the proposed joint location tracking and diarisation approach is able to perform comparably with other methods that use location information.
arXiv Detail & Related papers (2021-09-23T04:43:58Z) - Mundus vult decipi, ergo decipiatur: Visual Communication of Uncertainty
in Election Polls [56.8172499765118]
We discuss potential sources of bias in nowcasting and forecasting.
Concepts are presented to attenuate the issue of falsely perceived accuracy.
One key idea is the use of Probabilities of Events instead of party shares.
arXiv Detail & Related papers (2021-04-28T07:02:24Z) - A Hierarchical Network for Abstractive Meeting Summarization with
Cross-Domain Pretraining [52.11221075687124]
We propose a novel abstractive summary network that adapts to the meeting scenario.
We design a hierarchical structure to accommodate long meeting transcripts and a role vector to depict the difference among speakers.
Our model outperforms previous approaches in both automatic metrics and human evaluation.
arXiv Detail & Related papers (2020-04-04T21:00:41Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.