To see as a marker of contextual salience in romance languages : evidence from Acadian French and Brazilian Portuguese
Bibliographic record
Abstract
This paper discusses constructions found in Brazilian Portuguese (BP) and Acadian French (AF), in which the equivalents of to see accompanies a second verb in imperative utterances. In these constructions in BP and AF to see emphasizes the command expressed by the other verb. The BP construction can also have an additional interpretation, in which ve ‘seeimperative,2,singular’ has the meaning ‘to verify’. It is proposed that BP constructions can be associated to two different structures. The constructions with the ‘to verify’ meaning are treated as biclausal structures in which the verb ver ‘to see’ selects for a CP headed by the complementizer se ‘if’. As for the analysis of the emphatic order meaning associated to the BP and AF constructions, we adopt the proposals put forth in Speas & Tenny (2003) and Hill (2007, 2014) according to which conversational pragmatics is encoded in syntax as a predicative structure (Speech Act Projection - SAP) above CP. Following these ideas, we analyze BP and AF emphatic order constructions as monoclausal structures, where ve in BP and voir in AF are injunctive pragmatic markers that are externally merged into the SA head in order to encode a pragmatic relation.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".