Language affinity of heritage speakers in Western Canada: The link between language and emotions
Bibliographic record
Abstract
Heritage speakers (a type of bilingual who, typically learnt the heritage language at home and the dominant language outside the home) often feel different levels of connection (i.e., language affinity) to their heritage language. It has been theorized that bilinguals have two cognitive systems, one for each language and these systems stay in place throughout the lifetime of the speaker, no matter the trajectory of the languages (Dewaele, 2015). Research on heritage speakers in Canada has been limited to language use at home and in the community, as noted by Guardado (2018), leaving out research on heritage speakers and emotions. To address the paucity of research, the study described in this thesis investigates the language affinity of 25 adult heritage speakers of Spanish who are to varying degrees bilingual in Spanish and English and who reside in the Canadian province of Alberta. The participants completed an online bilingual language profile survey (BLP), an interview with the researcher to elicit immigration narratives and a word description task eliciting memories related to Spanish/English word pairs (e.g., house/casa). The quantitative analysis revealed that majority of the participants exhibited higher levels of emotions and in reaction to Spanish words compared to English words and different memories associated with each word in the word pair (i.e., one memory for ‘house’ and a different memory for ‘casa). The qualitative analysis delves into the factors that influenced these findings, which included language dominance, age of arrival to Canada and feeling culturally connected to the heritage language. This research has implications for the field of heritage language studies by showing the various factors that affect language affinity to the heritage and dominant language.
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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 | 0.001 |
| Science and technology studies | 0.010 | 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) | 0.003 | 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".