The challenges of fractionalized property rights in public‐private hybrid organizations: The good, the bad, and the ugly
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Policy designers seeking to harness profit‐driven efficiency for public purposes are increasingly creating organizations with fractionalized property rights that distribute “ownership” among public and private actors. The resulting hybrids are quite diverse, including mixed enterprises, public‐private partnerships, social entrepreneurship organizations, government‐sponsored enterprises, and various other hybrid forms. Marrying public purposes to private sector efficiency and strategic flexibility provides a tempting rationale for mixing public and private owners in hybrid organizations. Because public‐private hybrids involve fractionalized property rights, however, they exhibit tension among owners over both strategy and, more importantly, goals. To understand public‐private hybrids, we assess them in terms of six dimensions of property rights: fragmentation of ownership, clarity of allocation, cost of alienation, security from trespass, credibility of persistence, and autonomy (of both owners and managers). The unclear allocation of fractionalized ownership rights facilitates the appropriation of financial residuals and asset ownership opportunistically. Other weaknesses in the property rights configurations of public‐private hybrids create managerial dissonance or opportunistic behavior that typically leads to a narrowing of goals, but sometimes also to organizational failure.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 it