<i>Buddies</i> , <i>Dudes</i> , and <i>Bros</i> of Ontario: Trends and Patterns of Vocative Change
Bibliographic record
Abstract
This study tracks the use of familiarizer vocatives across the twentieth century in Ontario, Canada from a corpus comprising 11 million words of conversational interviews from individuals in eighteen communities, born between the 1880s and the 2000s. Vocatives are a richly variable grammatical category which are strongly tied to their sociolinguistic context. We focus here on the sub-category of familiarizers for birth years 1950-2004, which in these materials are almost entirely dominated by man , buddy , and dude . We extracted and coded several thousand vocative tokens, yielding 467 familiarizers. Random Forest modeling shows significant effects of birth year, gender, and community; but not education nor occupation. The dominant familiarizer man declines with the rise of buddy (outside Toronto) and dude (especially inside Toronto). Women use these incoming forms more than men do, perhaps as alternatives to the masculine-associated form man . The results show rapid change for familiarizers in patterns which parallel longstanding sociolinguistic principles.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".