Do Scale Frames Matter? Scale Frame Mismatches in the Decision Making Process of a "Mega Farm" in a Small Dutch Village
Bibliographic record
Abstract
Scale issues are an increasingly important feature of complex sustainability issues, but they are mostly taken for granted in policy processes. However, the scale at which a problem is defined as well as the scale at which it should be solved are potentially contentious issues. The framing of a problem as a local, regional, or global problem is not without consequences and influences processes of inclusion and exclusion. Little is known about the ways actors frame scales and the effect of different scale frames on decision making processes. This paper addresses the questions that different scale frames actors use and what the implications of scale frames are for policy processes. It does so by analyzing the scale frames deployed by different actors on the establishment of a so-called new mixed company or mega farm and the related decision making process in a Dutch municipality. We find that actors deploy different and conflicting scale frames, leading to scale frame mismatches. We conclude that scale frame mismatches play an important role in the stagnation of the decision making process.
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.
How this classification was reachedexpand
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 | 0.001 | 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) | 0.001 | 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 teacher head, 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".