Patterns of Interaction in a Computer Conference Transcript
Why this work is in the frame
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Bibliographic record
Abstract
An analysis of the interaction patterns in an online conference from a distance education graduate course was conducted, using an approach that focused on the transcript's interactional and structural features. A new tool for transcript analysis, the TAT (Transcript Analysis Tool), was used to analyze interactional features, while structural elements suggested by social network theory were examined. Analysis of the patterns of interaction in the conference showed interaction was variable, and that while all participants were engaged, intensity and persistence of participation were unequal among individual participants in several ways. The TAT showed the proportions of five major types of sentences in the transcript, corresponding to different modes of interaction (questions, statements, reflections, engaging comments, and quotations/citations). The findings showed that the TAT seemed to relate usefully to other work in this area, and that social network principles were valuable in the analysis of conference interaction.
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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 | 0.005 | 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 | 0.000 | 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) | 0.000 | 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