Understanding Collaborative Practice: Reading between the Lines Actions
Bibliographic record
Abstract
Collaboration is the central aspect of human practice; without it and the associated division of labor human society as we know it today would not exist. Successful collaboration enables a collective subject to produce more than the sum of what its members can do individually. But which conditions enable successful collaboration and how does it come about? In a case study of artifact designing in a class of sixth- and seventh-grade students, we articulate how the social interaction produces and reproduces the prerequisite and required intersubjectivity for successful collaboration and thereby constitutes a configuration of successful collaboration at two dominant modes of design practice. In face-to-face communication, human bodies produce a variation of available social and material resources and thereby concretely realize the generalized possibilities of making individual subjectivity available to others. This, we show, produces and reproduces intersubjectivity. During cooperative action, human bodies take up different parts of the collective labor and thereby achieve a division of labor, but the different contributions are accomplished into a collective one through human bodies in action, which constitutes a form of communication. We conclude that evaluating collaboration requires reading the productive value from communication and the communicative value from the division of labor, which, in dialectical unfolding of collaborative interactions, articulates itself in and as of creating new action possibilities (room to maneuver) through acting human bodies and therefore requires reading between the actions.
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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 | 0.010 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.007 | 0.059 |
| Scholarly communication | 0.014 | 0.024 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".