Bibliographic record
Abstract
The shortage of comparative studies on Caribbean migration is perhaps not surprising given that the region's general historiography remains fragmented by the borders of language, nation, and empire. However, in the past decade there has been an upsurge in comparative scholarship on Caribbean migration, particularly by those seeking to make connections between contemporary immigration in North America and Western Europe. Led by anthropologists and sociologists, recent studies have adopted differing comparative frameworks to analyse the cultural changes and social structures which have shaped the experiences of Afro-Caribbean migrants on both sides of the Atlantic. In advocating that histories of migration more consciously develop comparative approaches, Nancy Green has identified three distinct analytical frameworks to interpret population movements; linear, convergent and divergent comparisons. For Afro-Caribbean migration, the linear approach has been most often used by anthropologists seeking to highlight the cultural differences faced by the migrants between their societies of origin and those that they enter as immigrants. Sociologists have tended to construct divergent comparisons contrasting the experiences of Caribbean migrants between different societies to emphasise the impact of differing state policies or the similar labour markets faced by immigrants. While linear comparisons focus on the relationship between a single Caribbean territory and the metropole, divergent studies have been far more geographically ambitious. Covering Caribbean immigrants to the US, Canada, England, France, and the Netherlands, they often compare migrant groups drawn from different territories, ethnic groups, and social classes. This assumption of regional commonality however is highly problematic due to the historical distinctiveness of migration dynamics, trajectories, and systems for each Caribbean society. As Nancy Foner notes of her own comparative work on contemporary Jamaican migration, even within population movement from a single country there can be significant differences due to the social composition of migrant flows and historical change in both sending and receiving societies. Recognising the individuality of island environments and their migration systems does not necessarily preclude posing questions of ‘‘big structures, large processes, huge comparisons’’ (to borrow the Charles Tilly's phrase), however it does stress the importance of linking together sending and receiving societies in the same comparative framework.
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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 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".