I haven’t drank in weeks: the use of past tense forms as past participles in English corpora
Bibliographic record
Abstract
We investigate a relatively understudied phenomenon, the use of the (standard) past tense verb form as a (non-standard) past participle in English, as in I haven’t drank in weeks and refer to this phenomenon as “past tense spreading”. We explore this phenomenon in some familiar, large corpora of English, as well as utilizing the World Wide Web as a corpus through the Google search engine. The corpus-based approach allows us to examine details in the behaviors of many verbs across genres and to identify degrees of spreading among verbs. The web searches reveal differential behaviors for high-frequency and low-frequency verbs with respect to past tense spreading, an example, we claim, of Bybee’s (2006) Conserving Effect. Past tense spreading also occurs more than expected with modal auxiliaries, a pattern which would not be predicted based solely on the non-standard character of the phenomenon.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".