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Record W4411373800 · doi:10.1177/00754242251341318

<i>Buddies</i> , <i>Dudes</i> , and <i>Bros</i> of Ontario: Trends and Patterns of Vocative Change

2025· article· en· W4411373800 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of English Linguistics · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicLinguistic Variation and Morphology
Canadian institutionsUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsHistoryGeography

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.021
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.949
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.023
GPT teacher head0.304
Teacher spread0.281 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it