Translanguaging on Facebook: Exploring Australian Aboriginal Multilingual Competence in Technology-Enhanced Environments and Its Pedagogical Implications
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In this study, we explore how Aboriginal multilingual speakers use technology-enhanced environments, specifically Facebook, for their translanguaging practices. Using data collected from Facebook posts written by seven Aboriginal youth over a period of 18 months, we investigate how the participants move between Aboriginal English (AE) and Standard Australian English (SAE) creatively and strategically to express humour and group membership, and to identify as an Aboriginal person. We also observe how these practices have the potential to enhance rather than detract from their development of SAE. The findings of the study have important implications for teaching bilingual and bidialectal speakers in general and AE speakers in particular, highlighting the importance of creating a translanguaging space to enable them to maximize their knowledge and understanding of different subject matter and develop competencies in their various linguistic codes.
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.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it