Revisiting the Description of Tense in English
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The controversy surrounding the description of tense in English has remained because scholars have concentrated on carving descriptive niches for themselves rather than paying appropriate attention to its causative factor(s), resulting in three different descriptions: traditional, structural, and systemic. This paper identifies the genesis of the problems, points out how this hinders the attainment of descriptive accuracy, and proffers some solutions. It contends that arguments, such as whether or not there is a future tense for English, stem from the way tense is generally conceptualised. It examined ten standard definitions of tense and found that the keyword grammaticalisation is narrowly interpreted to mean the morphological only, whereas a language’s grammatical system consists of both syntactical and morphological aspects. The non-recognition of the syntactical component—even by grammarians that acknowledge future tense—is the root of the descriptive issues with tense. The paper proposes syntactical marking, achieved by placing the auxiliary WILL/SHALL or BE GOING TO before the base form verb, as the mechanism for future tense marking in English. In effect, English has a three-tense system, and its modes of marking are morphological (for present and past tenses) and syntactical (for future tense).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 it