Intersectional stigma and the arc of intranational migration: experiences of transgender adolescents and women who migrate within Peru
Bibliographic record
Abstract
BACKGROUND: Migration is recognized as a key determinant of health. Yet, limited research addresses the arc of intranational migration and, even less, the experiences of transgender (trans) adolescents and women migrants and the associated health vulnerabilities. Using intersectional stigma as a theoretical frame, this study seeks to better understand the sexual health vulnerabilities and needs of trans women migrants in Peru. METHODS: Between October and November 2016, in-depth interviews (n = 14) and two focus groups (n = 20) were conducted in Spanish with trans women in three Peruvian cities. To explore pre- and during migration experiences, focus groups were conducted in Pucallpa and Iquitos, key cities in the Amazon where trajectories often originate. To assess during migration and post-migration experiences, we conducted interviews in Pucallpa, Iquitos, and Lima to better understand processes of relocation. Audio files were transcribed verbatim and analysed via an immersion crystallization approach, an inductive and iterative process, using Dedoose (v.6.1.18). RESULTS: Participants described migration as an arc and, thus, results are presented in three phases: pre-migration; during migration; and post-migration. Intersectional stigma was identified as a transversal theme throughout the three stages of migration. The pre-migration stage was characterized by poverty, transphobia, and violence frequently motivating the decision to migrate to a larger city. Exploitation was also described as pervasive during migration and in relocation. Many participants spoke of their introduction to sex work during migration, as key to economic earning and associated violence (police, clients). CONCLUSION: Findings advance understandings of intranational migration and forced displacement as key determinants of trans women's health. Dimensions of violence at the intersection of classism and cisgenderism render trans women highly vulnerable at every step of their migratory journeys. Experiences of intranational mobility and relocation were described as uniquely tied to age, intersectional transphobic stigma, engagement in sex work, and multiple forms of violence, which impact and can magnify sexual health vulnerabilities for transgender women in Peru who migrated intranationally.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".