Invisibility and selectivity. Introduction to the special issue on Dutch overseas migration in the nineteenth and twentieth century
Bibliographic record
Abstract
Invisibility and selectivity. Introduction to the special issue on Dutch overseas emigration in the nineteenth and twentieth centuryThe contributors to this special issue describe the emigration of people from the Netherlands to the most important overseas destinations (the usa, Canada and Australia) in the nineteenth and the twentieth century.Part of the Dutch (overseas) emigrants formed strongly separated communities.Dutch emigrants were also rather invisible.In North America we see a combination of separateness and invisibility, in Australia mainly invisibility.Both in the nineteenth and in the twentieth century, migration was highly selective (with differences according to religion, class, ethnicity and gender).Only in the twentieth century (and especially after 1945) there was a strong influence of government policy on migration.In this issue, the comparison of emigration from one country -the Netherlands -to several destinations and the comparison over time show the influences of the societal context of the country of origin on the formation of Dutch emigrant communities.At a recent conference, organised by the Dutch Centre on Migration Studies, it was concluded that Dutch emigration is under-researched. 1 This special issue is the result of a call for papers in response to this observation, and attempts to fill at least part of this void. 2It presents five studies on Dutch
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.054 | 0.007 |
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".