Diversidad Sexual in Poza Rica and Coatzintla, Veracruz, Mexico
Bibliographic record
Abstract
This article is based on two months of ethnographic fieldwork done in 2017 in Poza Rica and Coatzintla, Veracruz, Mexico. I focus on the ways in which queer mestizos[i] contest, negotiate and mediate gender/sexual policing and how they challenge and produce/reproduce traditional gender roles and heteronormativity. I track these queer practices in contexts where institutions like family, marriage, church, and mass media, as well as cultural expressions like motherhood and language[ii] police alternative gender/sexual identifications and/or expressions. Gender and sexual policing are also mediated by the intersectionalities of gender, race-ethnicity, class, sex, and sexuality. I address queer (in)visibility and reveal how queer Mexicans make queer-worlds possible for themselves and publicly display what it means to be queer in these two towns. My findings reveal gender and sexual fluidity as well as emerging spaces that intersect with other practices for queer Mexicans. The data gathered also suggests terms of identification as a significant terrain fitting neatly into the paradigms of these two towns. [i] Mixed race as people part of the unmarked majority in these towns. [ii] Institutions and cultural expressions that work hand in hand in the construction and creation of people’s internalized homophobia.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".