Spatial Contexts of Language Shift and Heritage Language Retention within a Highly Diverse Population: Sydney, Australia
Bibliographic record
Abstract
Abstract In immigrant countries like America, Canada and Australia, heritage language retention and language shift (to the language of the receiving society) have long been associated with classical spatial theory, of initial segregation into inner city ethnic enclaves and subsequent intra‐urban migration into majority ‘white’ or ‘mainstream’ residential suburbia, respectively. First through third generation spatial dynamics of shift and retention in Sydney are analysed for the ten largest post‐1945 labour workforce immigrant streams from Europe and the ten post‐1960s mainly skilled immigrant streams from the Middle East and Asia. Quartile and diversity analyses show that the association of intergenerational heritage language retention with spatial concentration and language shift with spatial dispersion has been superceded by a new set of spatial dynamics. Instead, patterns of retention and shift are responding to high levels of population diversity and minority majority suburbs where culturally hegemonic mainstream and minority cultural groups are intermixed across 80 per cent of Sydney's suburbs.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| 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".