Subjunctive ‘Were’ vs. Indicative ‘Was’ Wish-Clauses: Why the Use of ‘Was’ Should Not Be Considered “Incorrect”
Bibliographic record
Abstract
While it is recognized that there has been a gradual shift from the subjunctive were to the indicative was in hypothetical, if-contexts (e.g., formulaic If I/he/she were x… statements) (e.g., Leech et al., 2009; Skevis, 2014), it is important to point out that the same kind of variation occurs in clauses of wishing (e.g., I/he/she wish(es) (that) I/he/she were the Queen/King of the world; I/he/she wish(es) (that) I/he/she was more affectionate). Similar to the former, variability between subjunctive and indicative in wish-clauses does not always constitute free variation. In other words, there are certain environments in which one mood may be preferable to the other. The present paper, thus, has as its objective to distinguish between the contexts in which each of the two forms tends to be used. Our discussion leads us to the conclusion that, wish-clauses with the subjunctive were (i.e., as related to desires pertaining to the pronouns ‘I’, ‘she’, and ‘he’) tend to be associated with desires that are unrealistic or quixotic, unattainable or impossible, and/or unnatural or extraordinary, whereas those with the indicative was, are generally tied to aspirations that are realistic or reasonable, attainable or possible, and/or natural or unexceptional.
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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 | 0.001 | 0.237 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".