Bibliographic record
Abstract
A growing field of research has paid attention to new forms of labour migration to and within the European Union (EU). This research has been characterized by increased circularity, flexible forms of employment, guest-worker programmes and seasonal work, often undocumented, primarily within the service, agriculture, forestry and construction sectors (Castree et al., 2004; Castles, 2006; McDowell et al., 2007; Neergaard, 2009). For many years, the media has reported on the inhumane work conditions for berry-pickers (mostly from the Isan region in Thailand but alsofrom Vietnam and China) and on repeated conflicts between berry companies and labour migrants in a number of Swedish municipalities. In light of these problems, labour unions and human rights organizations have criticized Sweden’s new 2008 Law on Labor Migration for its failure to secure protection for migrant labour. The rollout of neoliberal immigration policy (Peck and Tickell, 2002) and the rightward political shift in Europe and Sweden has undermined traditional regulatory and safety net regimes. Even so, Sweden still represents itself as a national identity that is based on democracy, citizenship and modernity (Ehn et al., 1993; Pred, 2000).
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".