The acquisition of object markers by Bemba-speaking children
Bibliographic record
Abstract
This study reports on three empirical studies which were undertaken to investigate the acquisition of object markers by Bemba speaking children and to compare the findings to age- matched French-speaking children. The motivation for the comparative study comes from the claim by Cocchi (2000) and Labelle (2008) that Bantu object markers and Romance clitics can be given a unitary analysis. In both language families as Cocchi (2000) points out, object , markers encode phi-features of corresponding lexical DPs, express syntactic relations of object, indirect objet, locative, and reflexive. They replace lexical arguments and have a similar syntactic distribution surfacing to the left of the verb. The study investigates the implications of these similarities in the acquisition of object markers in both language families. The Bemba spontaneous data shows similarities between Bemba and French children in terms of ages of acquisition and omission of object arguments. The data however, does not clearly show the delay in the acquisition of the object marker as opposed to the subject marker that is attested in child French. The elicitation production experiment shows that Bemba children do not randomly omit objects but appear to obey semantic and pragmatic constraints that license null objects in the target language whereas high rates of non-target omissions have been reported in child French. Bemba children, like French children, rejected the null object construction in a replication study of Griiter's (2006) Truth Value Judgment task (which had been used with French Canadian children of an equivalent age range). This is interpreted as showing that Bemba children like their French counterparts have no null object representation in their grammar. It is argued that because the null object construction is licit in adult Bemba (given the appropriate pragmatic constraints that license them), Bemba children do not have to unlearn it as it is not a defect in their grammar whereas French children will have to adjust to what is permitted in the target language.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".