Organizing for Circularity: Lifecycle Assessment, Systems Thinking, and Future-Orientation
Bibliographic record
Abstract
This panel symposium builds on existing work on circular economies by exploring approaches that support transitions toward circularity within and among organizations. To motivate research in this area, the panel symposium will unfold some of the complexities involved in organizing for circularity, focusing on three approaches: lifecycle assessment, systems thinking, and future-orientation. While each of these three approaches provides distinct ways that organizations can engage to achieve circularity, their clear interrelationships portray the complexities organizations face as they work to manage and organize their operations to reduce waste and ‘close the loop,’ and ultimately support resiliency in ecological systems. With a joint conversation and discussion among the panelists and audience, the symposium will challenge management scholars to consider how we can further develop management and organization research that advances circularity in organizations’ business models, practices, and processes, both in theory and practice.
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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 | 0.032 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.008 | 0.018 |
| Scholarly communication | 0.023 | 0.021 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.006 | 0.011 |
| Insufficient payload (model declined to judge) | 0.010 | 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".