Negotiating identities through pronouns of address in an immigrant community
Bibliographic record
Abstract
This article investigates forms of address, in particular the T/V distinction in German, in conversational interviews with German-speaking immigrants to English-speaking Canada and their descendants. From among 77 interviews conducted in two urban areas in Canada, we discuss instances of both the interactional use of and metalinguistic comments on forms of address. Our analysis is largely guided by conversation analysis and interactional sociolinguistics (e.g. Goodwin & Heritage 1990). Using Clyne, Norrby and Warren’s (2009) model of address as a backdrop, we investigate the construction of group identity and group socialization through the lens of positioning theory (e.g. van Langenhove and Harré 1993; Dailey-O’Cain and Liebscher 2009). This combination of analytical tools can explain shifts in both usage of and attitudes toward the T/V distinction that cannot be explained through language attrition arguments alone.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.016 | 0.013 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| 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".