Indexicality in Heritage Languages
Bibliographic record
Abstract
The variables examined in Chapters 5 and 6 show little evidence of being used for identity work. That is, they do not show (consistent) effects of ethnic orientation measures or speaker sex. This chapter explicitly contrasts variables that reflect indexicality (correlation to social factors) in homeland varieties to non-indexical variables. We begin by considering three indexical variables in Italian: (VOT) in unstressed-syllable contexts, (APOCOPE), and (R), illustrating the extent to which indexicality is maintained in the heritage variety. We find increasing use of the more standard variant only in (VOT). Furthermore, we find that younger speakers (both in homeland and heritage) favour the non-standard variant. We then compare the variable (R), the contrast between trill (or tap) and approximant variants, in Italian and Tagalog, where it has indexical value in the homeland varieties, to Russian and Ukrainian, where it does not. Finally, we consider two additional indexical variables: Cantonese denasalization and Korean VOT. We conclude by contrasting the behavior of homeland-indexicals in heritage varieties. The presence of indexical value in homeland varieties does not consistently influence outcomes in the heritage varieties.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".