Paradoxical practices of being with others: Some experiential dynamics at play while interacting across differences
Bibliographic record
Abstract
This paper presents findings from an experiment/workshop, which was motivated by the ever-increasing need in today’s fractured and complex world to foster engagements between people of diverse backgrounds, positions, and identities. The workshop taught and employed the PRISMA method, which provides a way for researcher-participants to study the experiential dynamics of participatory sense-making in social interactions. PRISMA can be seen as an analogue process technology or a participation technology. It is used to refract the experience of interaction dynamics as we engage in interactions. In this study, we invited participants to interact by drawing together on shared sheets of paper. We found that participants engaged in what we call paradoxical practices of being with each other, and that the materials through which people interacted influenced the emotions and sense-making that emerged. We present the research findings in a way that can be followed step by step by a reader in a traditional fashion, but also give the reader structured options to engage with the findings presented in a participatory way, true to the message of the paper. Finally, we draw conclusions from this work for the use of technology in human co-becoming, enactive ethics of participation and difference, and how to enhance interaction “literacy”. This research deepens the understanding of participatory sense-making, and sheds light on the interactive tensions at the roots of languaging and co-becoming. The findings contribute to both scientific knowledge and practical implications for navigating complex social interactions.
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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 | 0.018 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.033 |
| Scholarly communication | 0.010 | 0.013 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".