Canadian Dollar in the English Language Varieties: Corpus‑Based Study
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
The slang name for Canadian dollar loonie is a Canadianism used not only in spoken (Boberg, 2010: 121), but also in written texts such as Canadian news articles. While loonie is obviously taken for granted by Canadians, its occurrence in English texts published beyond Canada has hardly been in the focus of corpus-based studies. The goal of this study is to find out in what Canadian English written texts loonie occurs and whether it is encountered in the other varieties of English by researching the corpora adapted for web access at Brigham Young University (BYU), the Strathy Corpus of Canadian English (SCCE), the Corpus of Contemporary American English (COCA) and the corpus of Global Web-Based English (GloWbE). The first two corpora were searched to reveal the genres of the written texts loonie occurs and GloWbE – to see loonie used in the other varieties of English. The obtained results revealed that loonie occurs in such written texts as newspaper and magazine articles of SCCE and COCA predominantly in the contexts connected with money issues. Search of GloWbE showed the use of loonie in American and British mass media texts, which reveals that this Canadian slang name goes beyond Canadian texts and thus, as Davies (2005: 45) has stated ‘[...] few of us are cocooned from [...] vocabulary of the major international varieties of English’. These findings therefore call for more detailed research of the collocations containing loonie in various text types of different varieties of English.
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 | 0.001 | 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 | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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