Exploration of a quantitative method for measuring behaviors in conversation
Why this work is in the frame
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Bibliographic record
Abstract
Background: The literature on communication partner training (CPT) includes mainly studies with a small number of participants, because methods to measure changes in conversation pose practical challenges limiting the analysis of large samples.Aim: The aim of this study was to explore a quantitative procedure that would allow one to measure specific behavioral changes occurring in conversational exchanges involving a person with aphasia and a partner.Methods & Procedures: Forty-three problem-solving situations presented visually as well as with a simple written explanation were created to elicit conversation. In order to test the situations and develop further a procedure, we used data from a spouse of a man with aphasia during CPT delivered in a clinical setting. We developed specific definitions related to conversational behaviors targeted in the CPT. These defined behaviors were analyzed using a transcription-less method and an annotation software in the couple’s 39 conversation samples collected before, throughout, and 3-months post CPT. Reliability data were collected.Outcomes & Results: The procedure enabled us to create a protocol with two types of conversational situations and reliable definitions for measurement of conversational behaviors in a timely fashion. Pilot data of the measures are provided.Conclusions: It is expected that the method presented in this pilot study may be used to document the outcomes of CPT. It could be used with single-subject designs that require repeated measures and multiple group designs that require comparable data over large samples. It provides a method of data collection and analysis to better evaluate the effects of conversation-based treatments such as CPT.
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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 | 0.001 | 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 | 0.000 |
| 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 it