Real Utopias for Organizational Governance: Exploring Alternatives to the Corporation
Bibliographic record
Abstract
As management scholars grapple with grand societal challenges, there is a growing interest in imagining and exploring alternative forms of organizing. This symposium aims to advance the conversation on “real utopias” - radical yet plausible alternatives to the dominant social order that exist at the margins of society. Unlike previous approaches that either speculatively imagine alternatives or use marginal cases to inform mainstream organizations, we propose connecting the marginal cases and facilitating a conversation across empirical contexts whose practical and transformative implications have too often been constricted within theoretical silos. Inspired by Erik Olin Wright’s Real Utopias Project, this symposium brings together researchers studying radical alternatives to the shareholder-owned, profit-driven corporation. Our panel of scholars represents a range of divisions, and their work spans diverse empirical contexts including amongst others DAOs, cooperatives, social movements, indigenous groups, and religious communities. We propose that each of these disparate contexts constitute a piece of a larger puzzle - namely, what elements of imagined “desirable futures” are in fact viable, sustainable, and attainable for organizations here and now? This symposium will showcase different “real utopias” for governing organizations, followed by a facilitated comparative discussion. Our aim is to identify patterns across these cases, stimulate critical thinking about organizational forms, and potentially inspire new directions in management research and practice that take the margins seriously.
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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 | 0.009 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.067 |
| Scholarly communication | 0.015 | 0.016 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| 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".