Bibliographic record
Abstract
The usage of the Italian subjunctive, particularly in the context of embedded completive clause, can be considered a normative linguistic stereotype par excellence, to which speakers should pay particular attention if they want to speak ‘properly’. However, despite the massive effort of the normative enterprise, as well as the much scholarly attention garnered from linguists, overall consensus on what exactly constrains mood selection in discourse is not unanimous: whether it makes a semantic contribution, which verbs should trigger it, whether it signals more careful style. Grammarians are also concerned with the attrition of the subjunctive and its productivity in speech, fearing the loss of its supposed semantic contribution. Several studies have addressed these issues, but only a small amount of this body of work on Italian subjunctive has utilized a quantitative method and these assumptions have not been evaluated systematically under an accountable empirical methodology. The findings of the present variationist investigation illuminate new evidence in the patterning of subjunctive use in community-based spontaneous speech data and refuting the claims that it is productive and semantically-motivated. The analysis reveals a lexically motivated pattern of variation, i.e., the use of the subjunctive is mainly restricted to a handful of main clause verbs and a single embedded verb. Systematic analysis also shows a correlation between subjunctive choice and higher level of education, a social meaning that further strengthens the idea that no semantic contribution is made when the speaker opts for the subjunctive over the indicative, a phenomenon that is inherently variable.
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.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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 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".