Estructuración de la interpretación en los servicios públicos: el modelo de banco de intérpretes como una respuesta organizada a las necesidades de comunicación
Bibliographic record
Abstract
Globalisation urges governments to address equality in access to public services. Even though Public Service Interpreting (PSI) helps allophones to overcome the breach in communication, such services need a solid, organised structure to effectively respond to the current linguistic needs. This article presents the results of a comparative study of the healthcare interpreting services provided in Barcelona and Montreal which, by applying an indirect method of observation (interviews) to examine the aforementioned services, describes the existing PSI structures and organisations as narrated by their managers. Our conclusions draw attention to certain aspects of Barcelona’s interpreting services which, should they be modified, could be beneficial. Finally, the interpreters bank model settled in Montreal (and throughout Quebec) is suggested as a role model for Barcelona, that could contribute to structuring PSI services in Europe.
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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 | 0.013 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.009 | 0.082 |
| Scholarly communication | 0.022 | 0.010 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".