Cultural aspects of language heritage use and preservation: The impact of bilingualism on identity and social integration
Bibliographic record
Abstract
This study aimed to investigate the influence of proficiency in two or more languages on forming individual identity and social integration. To achieve this goal, a methodology was employed that was based on an analysis of the cultural aspects of bilingualism and an exploration of strategies for preserving cultural values in a linguistic environment. The research was conducted by analysing data from various countries, including Canada, Switzerland, the USA, South Korea, Vietnam, and others where bilingualism is prevalent. This allowed for the conclusion that bilingualism has a positive impact on preserving linguistic heritage and promoting harmonious social integration. The article delved into the cultural facets of bilingualism in detail, specifically strategies for preserving linguistic heritage and the interaction between ethnic groups in multilingual settings. The paper also considered multinational marriages as one aspect that influences cultural heritage and bilingualism. Multinational marriages can contribute to the preservation and development of the diversity of linguistic experiences within a family. The study examined how multinational marriages impact the choice of languages used within the family, and how this affects the identity and social integration of children growing up in such families. The findings of this study demonstrated that bilingual individuals possess a deeper understanding of cultural diversity, fostering more profound intercultural interactions and integration among various ethnic groups within society. Research has revealed that bilingual individuals exhibit more developed competencies and a higher level of adaptability in diverse cultural contexts. The results underscored the significance of supporting and promoting bilingualism as a tool for preserving cultural diversity and facilitating social integration. The findings of this study can be applied to educational programs, government and non-profit policies for preserving minority languages and social integration, as well as in international initiatives aimed at preserving linguistic diversity
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| 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".