Multicultural Australian English: The New Voice of Sydney – Supplementary Materials
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
Multicultural Australian English: The New Voice of Sydney (MAE-VoiS) is a project funded under the<i> </i>Australian Research Council Future Fellowship scheme. The aim of the project is to help us understand the speech patterns of young people from complex culturally and linguistically diverse communities across Sydney. Understanding how adolescents from different ethnicities use speech patterns to symbolically express their diverse sociocultural identities offers a window into understanding a rapidly changing Australian society.The MAE-VoiS corpus comprises audio recordings of 186 teenagers from 38 language backgrounds who each engaged in a picture naming task and a conversation with a peer facilitated by a local research assistant. Participants also completed an extensive ethnic orientation questionnaire and their parents completed a demographic/language survey. Speakers were located in five separate areas in Sydney that varied according to the dominant language backgrounds of speakers in the communities (four non-English dominant areas – Bankstown, Cabramatta/Fairfield, Inner West, Parramatta; and one English dominant area – Northern Beaches).The material in this record is a supplement to the corpus. It contains details of the following:a picture response task in which 183 single words and 41 short phrases were elicited through a set of images presented on a computer monitor. These items sampled the following characteristics specifically designed to target a wide range of phonetic features known to vary across individuals and groups: all AusE vowels in a targeted consonantal contexts; lexical stress patterns and word internal phonetic/phonological processes through a set of select polysyllabic words; and potential hiatus/juncture contexts through a set of short phrases;an Ethnic Orientation Questionnaire (modelled on Hoffman & Walker, 2010 and Clothier, 2019) to measure participants' orientation to their ethnicity, connection to their local community, and use of languages other than English;a Demographic survey to determine the child and parent place(s) of birth, gender, and languages spoken (including usage and domains of each language), parents’ age of arrival in Australia (if relevant), parents’ level of education, residence history, siblings and birth order, and whether there was any history of speech, hearing, or language problems/intervention. Clothier, J. (2019). Ethnolectal variability in Australian Englishes. In L. Willoughby & H. Manns (Eds.), <i>Australian English reimagined: Structure, features and developments</i> (pp. 155–172). Routledge.Hoffman, M. F., & Walker, J. A. (2010). Ethnolects and the city: Ethnic Orientation and linguistic variation in Toronto English<i>. Language Variation and Change, 22</i>, 37–67.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.009 |
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