Bibliographic record
Abstract
Southern Spain is one of the most attractive regions to live in and retire to for so-called lifestyle migrants in Europe. Most of them come to the Spanish ‘sunbelt’ from Great Britain and the Nordic countries and often spend the winters here. When strolling around the coastal town of Fuengirola in the province of Málaga, the presence of a Northern European migration is striking. Fuengirola is a major tourist resort with more than eight kilometres of white sandy beaches. A quarter of its 72,000 inhabitants come from other countries, mainly within Europe. Places like the London Pub, O’Haras Irish Pub, Nordic Video and Casa Nórdica, or organizations such as the Church of Sweden, Club Nórdico, Asociación Hispano Nórdica, AHN and The Swedish School, all give a glimpse into the cultural and institutionalized aspects of migrants’ national identities. During my fieldwork I observed that the Swedish/Scandinavian community in the area had its own radio station Kustradion 105 — the Coastal Radio at Costa del Sol — for ‘Coastal Swedes’. The community also organized a weekly dance orchestra night at Hotel Florida, frequented restaurants, cafés and shops serving or selling Swedish meat balls and gravlax (raw spiced salmon), and arranged special activities, such as a sewing circle (informally called ‘la junta’ from the Swedish word syjunta), quiz nights, a church choir, a group for genealogical research, and published several magazines, including En Sueco, Sydkusten (The South Coast) and the Swedish Magazine.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 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".