Bibliographic record
Abstract
This chapter reports on trends of continuity and divergence within the heritage generations examined and between heritage and homeland varieties. It discusses the degrees of similarities between the varieties in terms of (a) rates of use of innovative forms and (b) conditioning factors in the constraint hierarchy. The three variables examined are voice onset time (VOT, n=8,909), case-marking on nouns and pronouns (CASE, n=9,661), and variable presence of subject pronouns (PRODROP, n=9,190), each in three or more languages. The similarity in rates and conditioning effects across generations for (PRODROP), examined in seven languages, particularly contrasts with findings for this variable in experimental paradigms. Similarly, findings of little simplification or overgeneralization of the case system in three languages stands in contrast to the outcomes of several previous studies. (VOT) shows a drift toward (but not arriving at) English-like values for only some of the languages examined. For each variable, models are presented and interpreted; a table then details which aspects of the analysis contribute to the interpretation of stability and of each type of variation.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.051 | 0.004 |
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".