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
An ongoing academic debate shows that urban community gardening (CG) has diverse governance models with differing roles of city administration and citizens. This article uses an empirical case study conducted in the city of Tampere, Finland, to explore what I call the “operational space” of urban CG seen from the viewpoint of city officials. Two rounds of interviews were conducted with eight city officials, and a discourse analysis was applied for the data. As an analytic term developed in this article, the operational space emerges by administrative policies and practices that enable or constrain urban gardening under two general trends of urban governance: institutional ambiguity and neoliberal urban development. In this case, the operational space was rather rigid and narrow. The five main discourses on benefit, control of space, scarcity, unclarity, and newness referred to a clear aim to enable urban gardening. However, the discourses were restricted to strategic, limited, and instrumental levels, as the political-strategic aims of enabling urban gardening contradicted the administrative practices. The results show that cautiousness and unclarity in the administrative-political culture tend to lead to institutional ambiguity. In conclusion, operational space analysis is helpful to uncover the problems and possibilities between CG and city administration.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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