Migrantes cubanos en Montreal: una adaptación vista desde el habla
Bibliographic record
Abstract
espanolEn el siguiente trabajo presentamos un estudio sobre el habla de la comunidad cubana en Montreal que se centra, especialmente, en las posibles variaciones sufridas producto del contacto linguistico frances- espanol. Para ello, hemos analizado conversaciones semidirigidas grabadas (habla coloquial) con 19 cubanos residentes en Montreal. El habla de los cubanos participantes en este estudio presenta algunos de los rasgos caracteristicos de cualquier situacion de contacto linguistico (variaciones tanto en el nivel morfosintactico como en el nivel lexico-semantico), pero posee tambien peculiaridades debidas a la distancia tipologica de las lenguas implicadas (espanol- frances) y al contraste entre las sociedades de origen y de acogida, entre otros factores. EnglishCuban migrants in Montreal: an adaptation viewed from the speech perspective. In this paper we present a study of the speech of the Cuban community in Montreal that focus on possible contact-induced variations. To do this, we use data from a corpus collected by the researcher through recorded conversations (colloquial speech) with 19 Cubans currently living in Montreal. After analyzing the data, we have found that the speech of the Cuban participants in this study shows some of the characteristic features of any language contact situation (variations at the morphosyntactic and lexical-semantic levels), but also has peculiarities relating to the typological distance between the languages involved (Spanish-French) and the contrast between the societies, among other factors.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".