From the Netherlands to Canada : immigrant discourses on the transnational experience, race, and space
Bibliographic record
Abstract
In the wake of increased emigration from the Netherlands over the last several years, the aim of this thesis is to examine the main motivating factors that inform current Dutch migration practices to Canada. In this qualitative, multi-sited research comprised of 34 participants, considerable attention is given to examine the popular notions linking this observed increase in emigration to the growing politicization of issues related to immigration and racialization in the Netherlands itself, including the murder of politician Pirn Fortuyn and filmmaker Theo van Gogh. A transnational framework is used to address aspects related to the role of the media, the family, the maintenance of ties with the country of origin, the contestation of the notion of immigration, and the role of the nation-state in creating differentiated access to immigration. An overview of the motivations that informs the participants' decision to immigrate to Canada reveals that there is a cluster of overlapping reasons, often predicated on the historic notion that Holland is overpopulated. Motivations include a dislike of the current politicization of issues related to immigrants in Holland; a perceived lack of space and nature; frustration with rules and regulations; and, a perceived negative shift in socio-cultural attitude. In addition, current Dutch migration to Canada exemplifies a migration flow where economic motivators are no longer the centre point informing their decision to migrate, and the participants' migration practices also exemplify new considerations for how the concept of transmigrants is used in transnational migration studies.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.035 | 0.024 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".