Strategizing Together for a Better World: Institutional, Paradox and Practice Theories in Conversation
Bibliographic record
Abstract
In this article, based on a Symposium held at the 2022 Academy of Management Meeting, we present a moderated discussion between established scholars in the field of grand challenges—Shahzad (Shaz) Ansari, Natalie Slawinski, and Eero Vaara—focusing on the role of institutional, paradox, and practice theories in research on grand challenges. Our goal for the symposium was to bring these theoretical perspectives into conversation, reflect on the strengths and weaknesses of the lenses, and discuss potential intersections for future research on grand challenges. We present the panelists’ prepared remarks as well as the interactive discussion covering four topics: the limitations of existing concepts and theories, materiality, impact, and relations between theory and practice. As part of these four discussion topics, we also present questions and reflections from the audience. We conclude by summarizing insights gleaned from the symposium about critical gaps and avenues for future research.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".