Bibliographic record
Abstract
In his groundbreaking study of Martha’s Vineyard, William Labov (Labov 1963) showed that phonological variables can take on very textured local meanings. The use of a raised nucleus in /ay/, commonly referred to as “Canadian Raising ” is recognized all along the Atlantic coast as characteristic of various island dialects (Wolfram and Schilling-Estes 1996). In recent generations, the nucleus of this diphthong has been lowering to [a], presumably under the influence of the lowered variant that predominates in the mainland US and that characterizes mainstream US English. Labov’s study found that the height of this nucleus was functioning as a symbolic resource in the struggle over the fate of the island. In the process, the height of the nucleus in /ay / had taken on quite specific local meaning. It is on the nature of such meaning, and the mechanisms by which it is constructed, that I wish to focus in the following pages. When Labov arrived on Martha’s Vineyard, a growing tourist and summer home trade was bringing about major changes in the island’s life and economy, and the island’s inhabitants were split over the desirability of this mainland incursion. On the one hand, people engaged in the local fishing economy, dominated by old island families of English stock, saw this as a serious threat to local control of the island’s life and economy. Some others saw the summer trade as an opportunity for themselves and for the
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.010 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".