Drawing Out Democracy: The Role of Sortition in Preventing and Overcoming Organizational Degeneration in Worker-Owned Firms
Bibliographic record
Abstract
Fostering sustainable worker ownership and control of their organizations has long been an aspiration for many. Yet, the growth of worker-owned firms (WOFs) is often accompanied by organizational degeneration: the tendency for a small oligarchy of unrepresentative workers to control democratic structures at the expense of the participation of everyday workers. Prior research suggests that organizational degeneration occurs naturally as WOFs become larger and more complex. Building on and departing from this work, I argue in this essay that an important cause is likely to be current practice around how worker representatives are selected—specifically, the near-universal reliance on elections. As an alternative, I argue that the application of sortition—the use of lotteries—to select worker representatives in major decision-making bodies such as boards of directors and councils could help prevent and overcome organizational degeneration, while also offering additional social and business benefits for workers and their organizations.
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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 | 0.024 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.039 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.003 | 0.003 |
| 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".