Distributing leadership across people and objects in a collaborative research project
Bibliographic record
Abstract
This paper examines how distributed leadership involving actor–object couplings may contribute to coordinated action across disparate thought worlds. We draw on ideas from French pragmatist sociology and on a case study of a successful collaborative research project involving participants from academia, government and practice settings to show how various kinds of objects (including material artifacts, more abstract concepts and human-material assemblages such as committees and procedures) come to participate in the leadership practices of multiple individuals, allowing the connection among different worlds. We suggest that adjustments between groups involved in collaborative work do not necessarily occur through the sharing of a common vision but through the ability of leaders to translate projects in terms that can be appreciated by the groups that must be mobilized. These translation activities are distributed widely between leaders and objects that co-construct each other. Objects frame action and give meaning to people, participating in the construction of leaders' roles.
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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 | 0.052 | 0.047 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.013 | 0.021 |
| Scholarly communication | 0.013 | 0.013 |
| Open science | 0.002 | 0.020 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".