Supporting Culturally Responsive Assessment Practices With Preschoolers: Guidance From Methods in the Jamaican Context
Bibliographic record
Abstract
PURPOSE: There is a shortage of available methods to accurately inform the developmental status of children whose cultural and linguistic backgrounds vary from the mainstream. The purpose of this review article was to describe different approaches used to support the accurate characterization of speech, language, and functional communication in children speaking Jamaican Creole and English, an understudied paradigm in the speech pathology research. METHOD: = 15-33). Studies I and II described validation efforts about children's functional communication using the Intelligibility in Context Scale (ICS; speech) and the Focus on the Outcomes of Communication Under Six (FOCUS; speech and language). Study III described efforts to accurately characterize difference and disorder in children's expressive grammar using adapted scoring, along with adult models to contextualize child responses. Last, Study IV applied acoustic duration (e.g., whole word) and an adapted scoring protocol to inform variation in speech sound productions in the Jamaican context where a post-Creole continuum exists. RESULTS: Studies I and II offered promising psychometric evidence about the utility of the ICS and the FOCUS. Study III revealed strong sensitivity and specificity in classifying difference and disorder using adult models. Last, in Study IV, linguistically informed acoustic analyses and an adapted protocol captured variation in speech productions better than a standard approach. CONCLUSIONS: Applying culturally responsive methods can enhance the accurate characterization of speech, language, and functional communication in Jamaican children. The innovative methods used offer a model approach that could be applied to other linguistic contexts where a mismatch exists between speech-language pathologists and their clientele. PRESENTATION VIDEO: https://doi.org/10.23641/asha.23929461.
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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 | 0.123 | 0.131 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.005 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".