Enclitics in Croatian Language Teaching – Between Ideas and Practice
Bibliographic record
Abstract
This paper deals with the position of enclitics in the context of Croatian language teaching in secondary schools. Given that the written corpus shows considerable deviation from the standard interpretation of the Wackernagel’s law (Peti-Stantić 2007), our intention was to explore this phenomenon in the context of the Croatian language teachers’ attitude towards the rules of enclitics’ placement. The previous works in this field show different aspirations. While most contemporary grammarians (Babić et al. 2007, Barić et al. 2005, Težak, Babić 1994) favour the prosodic interpretation or Wackernagel’s law, according to which enclitics must follow the first stressed word in the sentence, some contemporary linguists (Peti-Stantić) advocate syntactic interpretation of this rule in Croatian language, which entails the enclitics being placed after the first stressed syntactic unit. The latter base their claims on the discrepancy between the prescribed norms and actual language use. Our work addresses precisely that issue – the relationship between the nominal and practical elements in teaching the Wackernagel’s law. The analysis of research results indicates that teachers are inclined towards prosodic interpretation of Wackernagel’s law but are not likely to correct their students when they practise it differently.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.016 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".