Vowel trajectories of African Americans in Georgia, USA
Bibliographic record
Abstract
Within the United States, dialectal variation is often characterized by vowel shifts: systematic differences in vowels' relative qualities and vowel-inherent dynamics. The African American Vowel Shift (AAVS), in particular, includes raising and fronting of front lax /ɪ ɛ æ/, among other features. The more recent pan-regional Low Back Merger Shift (LBMS), by contrast, includes lowering and backing of the same vowels. We evaluate these two shifts in an audio corpus of over 40 Black speakers from the Southern state of Georgia. Speakers, born between the 1930s and 2000, represent five demographic generations. Normalized formant values (F1,F2) from five temporal points per token are input to Generalized Additive Mixed Models (GAMMs). We test for significant changes in vowels' trajectories across time by fitting Year of Birth as a continuous smooth term. Additionally, we use linear mixed-effects modeling to test for raising versus lowering on the (F2–F1) front-vowel diagonal, across generations. Evidence from GAMMs and linear modeling indicates raised positions of /ɪ ɛ æ/ among older generations (1950s–1980s), followed by significant retraction from 1990–2000. These acoustic results are consistent with strengthening of the AAVS in the third quarter of the 20th Century, followed by a rapid transition to the pan-regional LBMS.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".