No Road to Paradise: María's Unbuilt Infrastructure.
Published In: Revista Hispánica Moderna (0034-9593), 2025, v. 78, n. 1. P. 68 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Seminario, Valeria 3 of 3
Abstract
This article reexamines Jorge Isaacs' María through the unexpected lens of Latin America's history of transportation infrastructure. Written while Isaacs oversaw the construction of Cauca's most coveted export road, I argue that the novel echoes broader anxieties about Colombia's inadequate transportation technologies. Efraín and María's romance—their tearful separations and longing for reunion—acquires new historical dimensions when read as superimposed over Cauca's key export route. The couple's struggle with separation underscores the urgency for infrastructure to bridge distances, aligning the reader's yearning for their reunion with the belief that connectivity is fundamental to happiness and prosperity. Identifying a pattern that links emotional excess to geographical distance, this article argues that María captures the fears that emerged in Latin America during the steam-powered transportation revolution, when the imperative to join an accelerating and globalizing world clashed with the challenges posed by trying landscapes and inadequate travel routes. Viewed from this perspective, the novel's melancholic nostalgia and sentimentality can be read as a response to the traumatic disjunction between the region's aspirations for integration into global capitalism and the reality of its infrastructural inadequacies that left the region locked in a peripheral position within the structures of capitalist growth. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Revista Hispánica Moderna (0034-9593). 2025/06, Vol. 78, Issue 1, p68
- Document Type:Article
- Subject Area:History
- Publication Date:2025
- ISSN:0034-9593
- DOI:10.1353/rhm.2025.a962253
- Accession Number:185994437
- Copyright Statement:Copyright of Revista Hispánica Moderna (0034-9593) is the property of University of Pennsylvania Press and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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