Talk in Interaction in the Speech—Language Pathology Clinic
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Clinical educators in speech–language pathology seek to provide the best possible opportunities for student clinicians to learn about clinical work and how the interaction between clinician and client is constructed. Observing and engaging in practice as apprentices under supervision are traditional means for students to develop knowledge, skills, and attitudes that are appropriate in professional work. In this article, we propose that learning about and applying clinical discourse analysis is an additional means to stimulate and deepen awareness of how clinicians interact with clients. The contexts of student-clinician education in Ireland are presented with regard to how discourse analysis is incorporated into the curriculum. Examples are presented and discussed for using discourse extracts to teach and demonstrate the negotiation of therapy roles. Recommendations for changing how clinicians talk are outlined. In conclusion, the benefits of analyzing clinical discourse to explicate therapy dynamics are described.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it