Evolving Jamaican migrant identities: Contrasts between Britain, Canada and the USA
Bibliographic record
Abstract
This paper uses the evidence of life-story interviews with migrant members of transnational Jamaican families who have kin in Britain and North America as well as Jamaica. The interviews show that Jamaicans who go to the USA usually strongly maintain a straightforward Jamaican identity, rejecting identification as Americans. Migrants to Britain and Canada, by contrast, more often develop various forms of mixed identity. The paper suggest that the most influential experiences which shape these differences are in the immigration processes, segregated housing, and the restricted mixed black-white sociability in the USA. Cet article utilise les donneées d'entretiens d'histoires de vie avec les membres migrants de familles jamaïcaines transnationales qui ont des parents au Royaume Uni et aux Etats Unis aussi bien qu'à la Jamaïque. Les entretiens montrent que les Jamaïcains qui vont aux Etats Unis conservent d'habitude une forte identiteé jamaïcaine, rejetant toute identification en tant qu'ameéricains. Par contre, les migrants au Royaume Uni et au Canada deéveloppent plus souvent diverses formes d'identiteé mixte. Cet article suggère que les expeériences qui ont le plus d'influence sur la formation de ces diffeérences sont les processus d'immigration, la seégreégation dans le logement et la sociabiliteé restreinte entre blancs et noirs aux Etats Unis.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.015 | 0.004 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| 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".