A preliminary adaptation of select subtests from the Western Aphasia battery – revised for the Franco-Ontarian population
Bibliographic record
Abstract
Standardized tests play a central role in how speech-language pathologists (SLPs) assess language disorders in adults in clinical settings. However, for bilingual populations-such as Franco-Ontarians-this process is hindered by a lack of culturally and linguistically appropriate tools, limited normative data, and few bilingual clinicians. Although many tests exist in English, few are available in French, particularly for speakers in minority-language contexts. The Western Aphasia Battery-Revised (WAB-R) is commonly used by SLPs in Ontario, and bilingual SLPs often rely on makeshift French translations to assess bilingual individuals, an approach that may affect assessment accuracy. The main objective was to develop a culturally and linguistically appropriate adaptation of the WAB-R for the Franco-Ontarian population. Only the language subtests were adapted; the apraxia, constructional, visuospatial, and calculation subtests were not included in this adaptation. The adaptation process followed Vallerand's cross-cultural back-translation methodology. The preliminary adaptation was pretested with 21 neurotypical bilingual Franco-Ontarian adults. Results showed that 73.9% of subtests underwent modifications to ensure linguistic equivalency or cultural relevance. Lexicalization of English words was frequently observed, particularly in naming and reactive speech tasks, highlighting English influence on Franco-Ontarian French. Two writing-related subtests-writing irregular words to dictation and writing non-words to dictation-scored below 90% and required revision (either modification of test items or expansion of accepted target responses). This research demonstrates that direct translations of assessment tools are inadequate for minority language speakers. Adapted tools must reflect local dialects, bilingualism, and cultural specificity.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".