Territorial Inequality Driven by Tourism: A Queer Mapping of Urban Space in Acapulco, Mexico
Bibliographic record
Abstract
Drawing on the life stories of nine LGBTTTIQ-identified people who have lived in Acapulco (Guerrero, Mexico), this article provides a queer mapping of this city, peripherally situated in the Global South yet with longstanding entangled transnational connections. The frame for this analysis is the concept of “territorial inequality,” a term coined by urbanism scholar Óscar Torres Arroyo, whose seminal work examined the emergence of this southern Mexican city as an urban space formed through a process of socioeconomic segregation driven by tourism. This article also responds to the call of queer urban scholars to look beyond the metropole for spaces of the political theorized on their own terms. In Acapulco, class, race, and nationality intersect with sexuality in ways that have made it a destination for some queers while also dangerous and unpredictable for others, a segregated sociopolitical space where norms of masculinity have collided with multiversal expressions of sexuality imbued with patterns of exploitation. A key destination during the 20th-century rise of international tourism and a place now securitized as “violent,” this urban space is also the site of evolving LGBTTTIQ movements, communities, and shifting patterns of queer life and queer tourism. This article reconsiders proposals made by queer theorists such as Lionel Cantú and Jasbir Puar regarding the complicated role of tourism in shaping sexualities, urbanization patterns, and state practices structured through colonial, neoliberal, and liberational processes, to theorize queer dimensions of the development of this city.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".