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Record W2317597510 · doi:10.5539/jsd.v9n2p193

Sustainable Development: The Role of Scientific Literature in Dutch Municipal Spatial Planning

2016· article· en· W2317597510 on OpenAlexvenueno aff
Lucas Vroom, Fenje M. van Straalen

Bibliographic record

VenueJournal of Sustainable Development · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicSustainability and Climate Change Governance
Canadian institutionsnot available
Fundersnot available
KeywordsSustainable developmentSpatial planningSustainabilityScientific literatureTrichotomy (philosophy)Political scienceEnvironmental planningScientific developmentRegional scienceSociologyDevelopment (topology)GeographyEpistemologyLaw

Abstract

fetched live from OpenAlex

The objective of this article is to show how Dutch municipalities use scientific literature about sustainable development in their spatial planning policies and processes. The approach to this research is twofold. First, we conducted a literature review that summarized the most important discourses in the international and Dutch literature. Secondly, we interviewed Dutch municipalities and asked them how they interpret and define sustainable (spatial) development, how they keep up with the quick developments surrounding sustainability and how they approach sustainable development in their own planning practices. Results show that many municipalities claimed to interpret sustainable development in a broad manner and claim to use a sufficient amount of scientific literature, but their planning practices suggest otherwise. We conclude that the trichotomy ‘international scientific literature – national professional literature - planning practice’ is not self-evident within Dutch sustainable (spatial) development.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.024
metaresearch head score (Gemma)0.038
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.128
Threshold uncertainty score0.254

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.038
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0080.024
Science and technology studies0.0090.020
Scholarly communication0.0230.014
Open science0.0020.008
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0050.000

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.

Opus teacher head0.009
GPT teacher head0.222
Teacher spread0.212 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2016
Admission routes1
Has abstractyes

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