Cinderella story retell task in Canadian French (Brisebois et al., 2023)
Bibliographic record
Abstract
Purpose: Main concept (MC) analysis is a well-documented method of discourse analysis in adults with and without brain injury. This study aims to develop a MC checklist that is culturally and linguistically adapted for Canadian French speakers and examine its reliability. We also documented microstructural properties and provide a normative reference in persons not brain injured (PNBIs).Method: Discourse samples from 43 PNBIs were collected. All participants completed the Cinderella story retell task twice. Manual transcription was performed for all samples. The 34 MCs for the Cinderella story retell task were adapted into Canadian French and used to score all transcripts. In addition, microstructural variables were extracted using Computerized Language Analysis (CLAN). Intraclass correlation coefficients were computed to assess interrater reliability for MC codes and microstructural variables. Test–retest reliability was assessed using intraclass correlations, Spearman’s rho correlations, and the Wilcoxon signed-ranks test. Bland–Altman plots were used to examine the agreement of the discourse measures between the two sessions.Results: The MC checklist for the Cinderella story retell task adapted for Canadian French speakers is provided. Good-to-excellent interrater reliability was obtained for most MC codes; however, reliability ranged from poor to excellent for the “inaccurate and incomplete” code. Microstructural variables demonstrated excellent interrater reliability. Test–retest reliability ranged from poor to excellent for all variables, with the majority falling between moderate and excellent. Bland–Altman plots illustrated the limits of agreement between test and retest.Conclusions: This study provides the MC checklist for clinicians and researchers working with Canadian French speakers when assessing discourse with the Cinderella story retell task. It also addresses the gap in available psychometric data regarding test–retest reliability in PNBIs.Supplemental Material S1. Best Practice Guidelines for Reporting Spoken Discourse in Aphasia and Neurogenic Communication Disorders.Supplemental Material S2. CLAN commands used to extract discourse variables in the transcripts and summary of interrater reliability results.Supplemental Material S3. MC scoring template.Supplemental Material S4. Canadian French adaptation of the Main concepts for the Cinderella retell task.Brisebois, A., Brambati, S. M., Jutras, C., Rochon, E., Leonard, C., Zumbansen, A., Anglade, C., & Marcotte, K. (2023). Adaptation and reliability of the Cinderella story retell task in Canadian French persons without brain injury. American Journal of Speech-Language Pathology, 32(6), 2871–2888. https://doi.org/10.1044/2023_AJSLP-23-00101
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".