Old Grammars New (?) Scope: Adjective Placement in Native and Non-Native Spanish
Bibliographic record
Abstract
Prior studies have examined the association between modifying adjective placement and interpretation in second language (L2) Spanish. These studies show evidence of convergence with native speaker’s intuitions, which is interpreted as restructuring of the underlying grammar. Two issues deserve further study: (i) there are debates on the nature of native speaker’s interpretations; (ii) previous results could be explained by a combination of explicit instruction and access to the first language (L1). The present study re-examines native and non-native intuitions on the interpretation of variable order adjectives in pre-nominal and post-nominal positions, and extends the domain of inquiry by asking if L2 learners have intuitions about the order of two-adjective sequences, which appear in mirror image order in English and Spanish (faded blue pants vs. pantalones azules desteñidos). Two-adjective sequences are rare in the input, not typically taught explicitly, and have a different word order that cannot be [partially] derived from the L1 subgrammar. Two groups of non-native speakers (n = 50) and native speaker controls (n = 15) participated in the study. Participants completed a preference task, testing the interaction between word order and restrictive/non-restrictive interpretation, and an acceptability judgement task, testing ordering intuitions for two-adjective sequences. Results of the preference task show that the majority of speakers, both native and non-native, prefer variable adjectives in a post-nominal position independent of interpretation. Results of the acceptability judgement task indicate that both native and non-native speakers prefer mirror image order. We conclude that these results support underlying grammar reanalysis in L2 speakers and indicate that the semantic distribution of variable adjectives is not fully complementary; rather, the post-nominal position is unmarked, and generally preferred by both native and non-native speakers.
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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 | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".