Bibliographic record
Abstract
Estudos apontam a migração internacional como resultado da insegurança econômica no país de origem. Este texto apresenta uma pesquisa realizada em Toronto, com um grupo de imigrantes brasileiros, cujo objetivo era entender a relação entre a migração internacional e a insegurança no Brasil. O resultado aponta para o fator econômico, que pode ser visto como um tópico da insegurança, ao lado da insegurança política, ambiental, social e física, que tem contribuído para a migração de brasileiros. Essas dimensões, intrínsecas e resultantes das relações sociais, podem ser melhoradas através do “uso da força”, bem como através da “educação”, se queremos construir a segurança humana no Brasil.Abstract: Studies point to international migration as a result of economic insecurity in the country of origin. This paper presents a research conducted in Toronto, with a group of Brazilian immigrants, intending to understand the relationship between the international migration and insecurity in Brazil. The results demonstrate that the economic factor can be seen as a topic of insecurity, besides the political, environmental, social and physical constrains, that have contributed to the migration of Brazilians. These intrinsic dimensions and resulting from social relations can be improved through “hard security” as well as through “education” if we want to build human security in Brazil.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.014 | 0.004 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".