Maladaptive state reinforcement of greenspace in racially marginalized neighborhoods: lessons from Louisville, Kentucky’s failed cooperative extension partnership
Bibliographic record
Abstract
Racially marginalized neighborhoods often lack equitable access to greenspace, despite government programs designed to provide this vital public good. We used the State-Reinforced Self-Governance (SRSG) Framework to evaluate and critique a failed greenspace decentralization program involving public–private partnership and community-based greenspace governance in Louisville, Kentucky, USA. State-reinforced self-governance involves decentralizing decision-making authority, empowering key stakeholders, and reinforcing their cooperation to manage feedback loops between public good provision and production. In doing so, the State (governments) seeks to enable sufficient authority, responsibility, and operational resources for polycentric self-governance. For 20 years, Louisville’s metro government informally sponsored a local administrative office of Kentucky’s Cooperative Extension Service—a federal/state program for agricultural research, education, and outreach—to oversee a community-based allotment garden program. We interviewed the program’s directors and analyzed its governing policies. We identified three major deficiencies in SRSG common to failed decentralization programs. First, the informal partnership lacked clearly defined, legally binding responsibilities—creating confusion and conflict. The partnership also lacked formal authorization and requirements for multi-actor cooperation (e.g., shared decision making, mutual monitoring)—undermining trust, collective problem solving, and compliance. Second, the Extension Office was underfunded and lacked essential operational capacities for land acquisition, protection, and management—creating a production crisis. Finally, as a subordinated administrative unit, the Office lacked authority to provision new policies to address known capacity limitations. These deficits severely limited the partnership’s transformative capacity, precipitating its collapse. According to the SRSG Framework, these arrangements exemplify a maladaptive, “responsibility-heavy” decentralization regime. Such systems are multi-centered but poorly coordinated and hierarchically governed. They impose responsibility on subordinate production agents under a guise of “polycentric self-governance,” without granting sufficient constitutional, administrative, or fiscal authority to function effectively. To facilitate theory development and institutional design, we contrast these arrangements with approaches that exemplify SRSG.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.021 | 0.009 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 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".