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 borderlands manifest themselves through encounters between people deemed to be in need of health care and health care providers (Mattingly, 2010). This article addresses the problem of inherent asymmetry in the clinical discourse between clinical providers, such as speech–language pathologists (SLPs), and persons with aphasia. Speech–language pathologists, communicating as experts, tend to dominate the discourse regarding the course of treatment, particularly with clients with aphasia who may lack the necessary communicative skills to participate in decision making. Such patterns of communication were apparent in a study reported here that involved thematic analysis of the views of 12 SLPs regarding involving people with aphasia in shared decision making and in analysis of 33 video recordings of these 12 SLPs and 28 people with aphasia during clinical interactions. Although the SLPs stated that they wanted to involve their clients in decision making and took steps to do so, the discourse sample analysis revealed that the SLPs controlled the interaction through their initiations, topic selection, and presentation of limited choices. Alternatives for supporting greater decision-making participation among people with aphasia with their clinicians are discussed.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it