Tiny Words, Big Meanings: An Analysis of Diminutives in Australian and Global Englishes
Bibliographic record
Abstract
This paper is a corpus-based, comparative study focusing on diminutive usage in Australian English (AusE) and six other English variants. The aim is to investigate Australian diminutives, compare their usage frequency between AusE and six other English variants, examine their collocates, and compare their frequency to the base form word. This study was conducted using the GloWbE corpus. Diminutives do not only imply smallness; they can also imply attitude, familiarity, intimacy, and/or colloquialization. Three diminutives, which are used in AusE, have been pre-selected by the author: brekkie/brekky, Aussie, and barbie. Moreover, the English language (and the AusE variety) uses the suffixes -ie/-y for nouns, among others, making them diminutives. AusE uses these suffixes far more often than the six other English variants investigated. The collocates that were found explain the meaning of the diminutives. The base form word is usually used more frequently than the diminutive. New Zealand English (NZE) also uses diminutives fairly, whereas American (AmE), Canadian (CanE), British (BrE), Irish (IE), and Indian English (IndE) use them seldomly.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| 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".