Imagens da língua e cultura portuguesas de falantes de português língua de herança nos Estados Unidos e e Canadá
Bibliographic record
Abstract
The images that individuals create of languages, people and cultures tend to refl ect their own communication and educational behaviours. These images can originate stereotypes, i.e., static, decontextualized, simplifi ed, and abbreviated images, present in common memory and accepted by particular groups (Castellotti & Moore 2002). Therefore, the diagnosis of images and perceptions that heritage language speakers associate with language and culture can enhance educational activity, particularly the comprehension of their directions and motivations, the adaptation of the teacher’s speech in classroom, as well as the creation and selection of didactic materials that aim to contribute to the (re)perspectivation of negative images or stereotype deconstruction. The main purpose of the present study is to diagnose and analyse quantitatively and qualitatively the images that heritage speakers of Portuguese language in North America possess of the Portuguese language and culture. To collect data, we created an anonymous online questionnaire composed of 19 questions signifi cantly related to the respondents’ contact with the language and Portuguese communities, as well as their perceptions of Portuguese population, language and culture. The questionnaire was taken by 10 heritage speakers (belonging to the second and third generation of Portuguese emigrants) who reside in the United States and Canada, countries with a signifi cant presence of Portuguese communities. The data reveals a collective thought of the respondents, composed of homogenous, crystallized, and stereotyped images regarding the Portuguese language and its utility, as well as its people and culture
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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 | 0.003 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".