Social Aspects of Cognitive Linguistics: Studying Language Attitudes and Identity
Bibliographic record
Abstract
The analysis of language attitudes seeks to elucidate various dimensions of linguistic functioning, particularly where the social dimensions of discourse are manifest, such as lexical encoding, interaction positioning, and discursive strategies. It also considers elements aligned with cognitive models that shape language use in specific contexts, cultivated through socialization and the formation of social identity. Linguistic identity, a multifaceted construct, encompasses both linguistic and cultural knowledge and plays a key role in shaping personality. This study examines the linguistic identity of plurilingual students from various Ukrainian higher education institutions, assessing how plurilingualism impacts their identity. Using qualitative analysis of survey data from 31 students collected in autumn 2023, the study explores themes such as the influence of linguistic environments on plurilingualism, language attitudes, and self-identification. The findings indicate that all languages spoken by an individual contribute to shaping their linguistic identity, with self-identification as bilingual or plurilingual influenced by personal language proficiency and relevant language environments. The results support the idea that linguistic identity evolves over time, highlighting the dynamic nature of language and identity in response to varying social contexts.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".