Critical Perspectives in Speech-Language Therapy: Towards Inclusive and Empowering Language Practices
Bibliographic record
Abstract
This conceptual paper critically examines the use of traditional medicalized terminology in speech-language therapy, with a particular focus on the Quebec context. It highlights how current language practices, rooted in a medical model of disability, often marginalize individuals with communication differences such as stuttering, autism, and aphasia by pathologizing these variations. Drawing on contemporary frameworks such as the social model of disability, neurodiversity, and “diversité capacitaire” (a French term that translates to “capacity diversity” or “ability diversity”, emphasizing the richness of diverse abilities and communication styles), the article advocates for more inclusive and empowering language that respects and reflects communicative diversity. The authors emphasize the importance of participatory approaches, including consultation with the communities directly involved and the establishment of terminological committees, to develop respectful and affirming language. Ultimately, this paper calls for a shift in speech-language therapy practices to promote a more inclusive understanding of communication, enabling individuals with communication differences to fully participate in society.
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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 | 0.029 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.034 | 0.130 |
| Scholarly communication | 0.020 | 0.012 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.009 | 0.014 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".