Everything Irie: Examining the Occurrence of Jamaican Patois in the Greater Toronto Area
Bibliographic record
Abstract
This Major Research Project (MRP) examines the occurrence of Jamaican patois in the Greater Toronto Area (GTA) among people of a Caribbean ethnic or cultural background. This project supplies data on the demographic characteristics of Jamaican patois speakers in the GTA and the situational contexts in which they use the language. The study has been developed as a pilot and foundation for further qualitative research in the field of communication to investigate the motivating factors of Jamaican patois use in the GTA. This MRP uses the theoretical frameworks of Code Switching (Deubers, 2014; Langman, 2001), Communication Accommodation Theory (Giles, 2008; Gallois, Ogay & Giles, 2005; Giles & Ogay, 2007), and Co-Cultural Communication Theory (Orbe 1996, 1998) to analyze the answers received in response to a quantitative online survey questionnaire. According to survey responses, participants adjust their use of Jamaican patois in the GTA as a means of assimilation and social conformity. Overall, research participants speak the most Jamaican patois at home and while socializing and/or engaging in activities outside of the home. Participants with a higher level of income and education speak less Jamaican patois regardless of physical or social contexts and a significant number of participants speak Jamaican patois if it works to their favour. These findings indicate that, while Jamaican patois use by Caribbean’s in the GTA is associated with a lower level of income and education, the intra- and possibly intercultural affordances of the language merit further study.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".