Argument Omission in Portuguese as a Second Language
Bibliographic record
Abstract
Interlanguage grammars are complex and are shaped by a combination of general learnability issues such as transfer and generalization, and characteristics of the individual learner, such as motivation and degree of extroversion (Lightbown & Spada, 2013; Selinker, 1972). The individual factors may be particularly salient in classroom learning, where motivation plays an important role in language learning. The question is whether they also play a role in areas that are implicit, perhaps occasionally touched on by the instructor but not necessarily part of the curriculum. Furthermore, the relationship between the different factors may change according to the proficiency level of the learners. This paper will examine the interplay of these factors by examining the acquisition of subject and object omission in Portuguese as a second language.\nUnlike English, Portuguese is a null subject language. This is a property that is taught in the education system up to a certain point. What is not necessarily taught, however, is that the choice of when to drop or include a subject must follow information structure rules: if there is no topic shift or contrastive focus, subjects are omitted, if there is contrastive focus, the subject pronoun should be used. This is illustrated in (1) (Rothman, 2009; Sorace, Serratrice, Filiaci, & Baldo, 2009). At the same time, Brazilian Portuguese allows third person objects to be dropped rather freely, again when the meaning is recoverable from the context (2) (European Portuguese drops objects also, but less freely). In both cases, we are dealing with complex grammar, in which syntax and pragmatics interact, constituting what is referred to as an interface (Sorace, 2011). The pragmatics is generally not taught in either case. The syntax of object drop is also not part of the curriculum.\nWe will present an empirical study that examined proficiency of subject and object drop at two levels, beginner learners (n=15) and intermediate learners (n=10). Participants completed a grammaticality judgment task that included appropriate and inappropriate pronouns, and a task in which context was created using pictures followed by a question, and the participants had to choose the preferred response(s). Participants also answered a motivation questionnaire, and a questionnaire intended to determine their degree of extroversion/introversion. Results are analyzed regarding accuracy at the different levels, and correlations between correct responses and the psychological tests. Factors such as transfer, complexity, and frequency of the input will be discussed.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".