arXiv subjects

Carlos Navarrete

Publications and source records attributed to Carlos Navarrete.

4 recordsLinked to original sources

arXiv2025

Talent is Everywhere, Mobility is Not: Mapping the Topological Anchors of Educational Pathways

The relationship between socioeconomic background, academic performance, and post-secondary educational outcomes remains a significant concern for policymakers and researchers globally. While the literature often relies on self-reported or aggregate data, its ability to trace individual pathways limits these studies. Here, we analyze administrative records from over 2.7 million Chilean students (2021-2024) to map post-secondary trajectories across the entire education system. Using machine learning, we identify seven distinct student archetypes and introduce the Educational Space, a two-dimensional representation of students based on academic performance and family background. We show that, despite comparable academic abilities, students follow markedly different enrollment patterns, career choices, and cross-regional migration behaviors depending on their socioeconomic origins and position in the educational space. For instance, high-achieving, low-income students tend to remain in regional institutions, while their affluent peers are more geographically mobile. Our approach provides a scalable framework applicable worldwide for using administrative data to uncover structural constraints on educational mobility and inform policies aimed at reducing spatial and social inequality.

cs.CY↗

arXiv2023

Mapping Election Polarization and Competitiveness using Election Results

The simplified hypothesis that an election is polarized as an explanation of recent electoral outcomes worldwide is centered on perceptions of voting patterns rather than ideological data from the electorate. While the literature focuses on measuring polarization using ideological-like data from electoral studies-which are limited to economically advantageous countries and are representative mostly to national scales-we argue that, in fact, voting patterns can lead to mapping effective proxies of citizen divisions on election day. This paper perspectives two complementary concepts, Election Polarization (EP) and Election Competitiveness (EC), as a means to understand voting patterns on Election Day. We present an agnostic approach that relies solely on election data and validate it using synthetic and real-world election data across 13 countries in the Eurozone, North America, Latin America, and New Zealand. Overall, we find that we can label and distinguish expectations of polarized and competitive elections in these countries, and we report that EP positively correlates with a metric of political polarization in the U.S., unlocking opportunities for studies of polarization at the regional level and for lower/middle-income countries where electoral studies are available, but surveys are limited.

cs.CY↗

arXiv2023

Measuring and Controlling Divisiveness in Rank Aggregation

In rank aggregation, members of a population rank issues to decide which are collectively preferred. We focus instead on identifying divisive issues that express disagreements among the preferences of individuals. We analyse the properties of our divisiveness measures and their relation to existing notions of polarisation. We also study their robustness under incomplete preferences and algorithms for control and manipulation of divisiveness. Our results advance our understanding of how to quantify disagreements in collective decision-making.

cs.MA↗

arXiv2022

Understanding Political Divisiveness using Online Participation data from the 2022 French and Brazilian Presidential Elections

Digital technologies can augment civic participation by facilitating the expression of detailed political preferences. Yet, digital participation efforts often rely on methods optimized for elections involving a few candidates. Here we present data collected in an online experiment where participants built personalized government programs by combining policies proposed by the candidates of the 2022 French and Brazilian presidential elections. We use this data to explore aggregates complementing those used in social choice theory, finding that a metric of divisiveness, which is uncorrelated with traditional aggregation functions, can identify polarizing proposals. These metrics provide a score for the divisiveness of each proposal that can be estimated in the absence of data on the demographic characteristics of participants and that explains the issues that divide a population. These findings suggest divisiveness metrics can be useful complements to traditional aggregation functions in direct forms of digital participation.

cs.CY↗