Heritage Language Learners and Automaticity: The Use of "por" and "para"
Bibliographic record
Abstract
The purpose of this study is to investigate the use of the Spanish prepositions por and para (P&P) by heritage-language (HL) learners to analyze whether they demonstrate automaticity in their application, as is common with L1 Spanish speakers (i.e. “it just sounds right”), or if they rely on the conscious, declarative knowledge of the prescriptive uses of these prepositions, as is common with speakers for whom Spanish is an L2. Upper and lower HL learners and upper and lower FL learners (non-HL learners) were asked to complete a cloze test and a grammaticality judgment task and were asked to explain their judgments. The explanations given by students provide a glimpse into the type of knowledge, whether declarative or procedural, that students tap into when using P&P. This study found that while FL learners relied on declarative knowledge in the application of P&P, HL learners demonstrated a level of automaticity and procedural knowledge in their use of these prepositions. This suggests that HL learners have internalized the uses of P&P though communicative exposure throughout their childhood, which may be more effective than the explicit instruction FL learners have received on these structures. This study aims to add to the growing body of literature on heritage language processes and development.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".