Revisiting a Dialogue: Collaborative and Dialogical Practices in Motion
Bibliographic record
Abstract
The authors and eight other colleagues from Yucatan in Mexico, with an average of ten years of training and professional experience with collaborative and dialogic practices (CDP), carried out an investigation on how the practitioners of these practices develop a critical view of their professional activity. Our research is framed in discursive psychology, since we identify ourselves with the critical reflections about practicing. We reflect on how to adopt the discourse of the CDP, how it can be associated with the discomfort that one has with positivist discourses, as ways of challenging what is established, and even as a form of freedom. In addition, we review the CDP as a stance and a form of analysis, as well as offer our reflections on its possible colonizing and political effects. We offer some practical implications as a form of updating to face the new dilemmas that life throws at us.
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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 | 0.015 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.023 | 0.026 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.005 | 0.005 |
| 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 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".