A Certain Future: Epistemicity, Prediction, and Assertion in Iberian Spanish Future Expression
Bibliographic record
Abstract
Abstract The choice of future construction in Romance languages with variable expression is complex, and several factors have been shown or hypothesized to influence this choice (e.g. Aaron 2006, 2010 and Poplack & Malvar 2007). One factor stands out time and time again, though scholars do not always associate it with the same form: certainty. Using corpus-based quantitative methods, the role of certainty in Iberian Spanish future form variation is examined. The semantics of futurity and epistemic modality are discussed, with particular reference to the Spanish synthetic, or morphological, future. Then, the onset of non-future-reference use of the Synthetic Future as an epistemic marker is described, and viewed in light of the role of epistemicity in the possible strengthening of the semantics of “certainty” with the Spanish Periphrastic Future. Finally, diachronic evidence from distributional patterns in grammatical person, verb class and clause type is presented, which suggests that speakers associate the periphrastic construction with “certainty” and, increasingly, the synthetic construction with “uncertainty.” It is suggested that functional competition with innovative forms can breathe new life into older forms, sparking further grammaticalization.
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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 | 0.003 | 0.005 |
| 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 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".