Intergenerational Family Language Policy Retention Through the Lens of the Theory of Planned Behaviour
Bibliographic record
Abstract
The retention of languages is a topic that is relevant to many bilingual and multilingual Canadian families. To navigate the retention of multiple languages, some parents choose to enforce rules concerning the appropriate use of languages. These normative language rules, termed family language policies (FLPs), can be articulated explicitly or demonstrated more implicitly. There is a lack of research examining the cross-generational retention of FLPs, and this study addresses this gap by investigating emerging adults’ past and current language use experiences and their plans for future language use. Multilingual Canadian adults (N = 670) between the ages of 17 and 29 participated in an online survey that focused on their experiences of being multilingual in childhood and adulthood, including opportunities, challenges, and anxieties, as well as their intentions to retain their language policies in their future homes. Using the Theory of Planned Behaviour as a theoretical lens, it was hypothesized that participants’ beliefs towards language retention (i.e., opportunities, challenges, and heritage language attitudes), the subjective norms they are exposed to (i.e., heritage language norms and childhood FLPs), and their perceived behavioural control (i.e., heritage language anxiety and heritage language self-competence) predict their intention to retain the language in the future (i.e., personal heritage language and FLP retention with significant other and future children influences). The results of structural equation modelling indicated that language beliefs play a key role in heritage language retention: participants who associate more opportunities than challenges to speaking multiple languages are more likely to hold positive attitudes towards their heritage language, which in turn makes them more likely to retain their heritage language, to choose a romantic partner with a similar linguistic background and plan to raise children in a multilingual household. Unexpectedly, normative beliefs significantly predicted heritage language attitudes, while perceived opportunities directly predicted heritage language retention. This pattern of findings highlights the difference between retaining a language for social advantage versus personal significance. Lastly, FLP retention was most strongly predicted by high levels of heritage language self-competence and childhood FLP exposure, highlighting the benefits of either implicit or explicit early language use rules as a model for future FLP strategies. The results of this study provide insights into how heritage languages and FLPs can be retained across generations.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".