El<i> year abroad</i> al dominilingüístic català
Bibliographic record
Abstract
CHARACTERISTICS OF THE LINGUISTIC LANDSCAPE OF THE PORTUGUESE QUARTER IN HAMBURGWith the development of social relations, the number of different graphic signs that convey information increases. Landry and Bourhis (1997) consider that the ensemble of verbal signs in public space creates the linguistic landscape of a place. The informative function is not the only one performed by these signs. This study analyses the linguistic landscape of the Portuguese Quarter in Hamburg. This is an area colonised by immigrants, mainly from the Iberian Peninsula. Today, the main economic activity in the area is gastronomy. Most of the establishments are named in Romance languages, which is purely symbolic. The verbal signs in German have an informative character. On the menus and other information at eye level of the customers, it is much more obvious that German is dominant and the signs in the Romance languages serve to relate the dishes to the respective cuisines and to create or emphasise the ambience of the interior. What may come as a surprise, especially to a foreign tourist, is that in the Portuguese Quarter, although it is considered an attraction, there are not many verbal signs in English, except for a relatively limited offer aimed at foreign tourists. The multilingualism of the Portuguese Quarter is an attempt to preserve the character and tradition of the area.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.014 | 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".