Bibliographic record
Abstract
One of the most dramatic discourse–pragmatic changes in twentieth–century English has progressed under the radar of laypeople and (until recently) linguists: the rise of um as the predominant variant of the “filled pause” variable (UHM) at the expense of uh. We investigate UHM at an early stage of change to determine what triggered its rise. We employ the variationist method to examine UHM in the Farm Work and Farm Life Since 1890 corpus of oral histories (recorded in 1984 with elderly farmers in Ontario, Canada). Nearly 5,000 tokens were extracted and coded for speaker birth year, gender, region, and utterance position. The overall frequency of um among the farmers is 11 percent. We find no significant effect of gender (12 percent for women, 10 percent for men). In one region, there is an effect of birth year. Lastly, we find no effect of utterance position. Looking at the frequency of each variant per 1,000 words, however, we see that, while the rate of um remains relatively stable, the rate of uh increases rapidly with year of birth, particularly with non–initial tokens produced by female speakers. Our results indicate that this data covers the first stage of this change.
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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 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".