Word‐finding behaviours in narration for typically developing French speakers of school age
Bibliographic record
Abstract
BACKGROUND: Research in word-finding difficulties is sparse, especially in languages other than English. As a result, the factors associated with the frequency of word-finding behaviours are poorly understood, particularly in discourse. AIMS: This exploratory study is the first to collect data relative to the expected frequency of word-finding behaviours in narration for French speakers aged 7-12 years old with typical development; and (2) to identify the factors associated with the frequency of word-finding behaviours in narration. We hypothesized that sociodemographic characteristics, language abilities and characteristics of the spoken productions could be linked to word-finding behaviours. METHODS & PROCEDURES: The participants consisted of 61 French-speaking children aged 7-12 years old (M = 9;09 years, SD = 1;06 years) with typical development. Children were asked to complete a receptive vocabulary task, a non-word-repetition task and two narrative tasks. The children's narrative samples were coded using a discourse analysis of word-finding behaviours, as described by Diane J. German. OUTCOMES & RESULTS: Participants produced 39% of T-units with least one word-finding behaviour, which included relatively frequent use of repetitions and word reformulations. Regression analyses revealed that the participants' gender was the only significant variable associated with the frequency of word-finding behaviours in narration. Boys produced a higher percentage of T-units with at least one word-finding behaviour. Post-hoc analyses suggested that gender differences reflected differences in repetitions and word reformulations. Boys and girls did not differ on any other language measures collected. CONCLUSIONS & IMPLICATIONS: Speech-language pathologists may want to take into account a child's gender when assessing word-finding difficulties in narration. Additional studies are needed to understand whether this finding extends to other word-finding tasks and to children with word-finding difficulties. WHAT THIS PAPER ADDS: What is already known on the subject Studies in English have identified that analyses of word-finding behaviours in discourse can be used to correctly identify children with word-finding difficulties. Studies are needed in other languages to determine if this observation holds true across languages. Moreover, the factors associated with the frequency of word-finding behaviours in discourse are poorly understood. What this paper adds to existing knowledge The frequency of word-finding difficulties in narration was higher in our study of French-speaking children than in previous studies of English. Gender was the only factor associated with the frequency of word-finding difficulties. What are the potential or actual clinical implications of this work? The language and task used to assess word-finding skills as well as the child's gender may be important to take into account when assessing word-finding difficulties based on word-finding behaviours.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".