HAITIAN IMMIGRATION IN CAMPINAS, SÃO PAULO: A STUDY ON THE ROLE OF MIGRATION PROJECTS
Bibliographic record
Abstract
This work derives from doctoral research completed in 2024. The research investigates the migration project of Haitian immigrants in Campinas, São Paulo, analyzing its structural elements, strategies, and future prospects. The migration projects will analyze the possibilities and constraints available at the destination, according to the experience of the pioneer migrants who made the first trip and exchanged experiences about this journey. The analysis of the migration projects of Haitians in Campinas/SP, based on fieldwork and bibliographic review, reveals the complexity of these immigrants' trajectories and their adaptation strategies. The concepts of migrant autonomy (Ma Mung, 2009) and circular knowledge (Tarrius, 2002) help to understand how these immigrants construct their migration projects and their migration ideologies. One of the main elements present in the construction of Haitian migratory projects is the labor aspect, in which paid work is fundamental for sending remittances to family members who remained in the country of origin. In the formulation of future perspectives, there is mainly a desire to migrate to countries in the global north, such as Canada, France, and the US, classic destinations for Haitian immigration. Haitian migration projects in Campinas/SP show that migration is not an isolated event, but a continuous and complex process of learning and adaptation.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.011 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 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".