Integrating spatial planning and energy policy in The Netherlands: challenges and lessons for societal energy transitions
Bibliographic record
Abstract
Despite The Netherlands' advanced spatial planning system and robust energy infrastructure, attempts to integrate energy policy and spatial planning for energy transition faced significant challenges. This paper examines these efforts and their impact on both systems within nation-wide discussions, using social systems theory to explore why a cohesive strategy failed to emerge. It draws on Luhmann’s theory of social systems and his concept of irritations, combined with a theory-informed thematic analysis, to understand the communications and perturbations between energy planning and spatial planning. The paper argues that the planning and energy systems were unable to adequately understand and coordinate with each other, partly due to the lack of a unifying perspective and the inherent tensions within each system. These challenges hindered the formulation of effective energy transition strategies on a policy level. To distinguish between the degree to which communications of energy planning organizations successfully initiated internal reflections on and revisions of spatial planning organizations’ interests, operations, and priorities, we introduced three types of perturbations, so-called ‘irritations’: incomprehensible, inapt and interpretive irritations. The Dutch experience offers broader insights into the complexities of aligning spatial planning with energy policy in the pursuit of energy transition.
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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 | 0.011 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.004 | 0.012 |
| Scholarly communication | 0.013 | 0.010 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".