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Record W2106288150 · doi:10.1080/09654313.2014.945818

Linking Agricultural Policies with Decision-Making: A Spatial Approach

2014· article· en· W2106288150 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEuropean Planning Studies · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicLand Use and Ecosystem Services
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsUrban sprawlAgricultureLand useAgricultural landAppropriationContext (archaeology)Environmental planningPopulationLand coverSustainabilityEnvironmental resource managementBusinessGeographyRegional scienceNatural resource economicsEconomics

Abstract

fetched live from OpenAlex

The loss of agricultural land and its implications have been of great concern in the last decade. By undertaking a spatial analysis of the appropriation of agricultural land for urban use with an overlay of population and urban data, a focus on the consequences of certain regulations on the dynamics of land-use change is explored. This is achieved by integration of data inventories of agricultural land use for Portugal, and linking this information with CORINE Land Cover data as to assess change in the Algarve. An integrated assessment of agricultural land loss follows, undermined by the consequences of urban sprawl. In this sense, this paper expands on the currently existing decrees which provide support to sustainable development in the region while providing a qualitative assessment of future roles based on ethical values and economic efficiency and offering a feasible framework for policy-makers regarding the trends of urban/agricultural dichotomy in a planning and decision-making context.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.106
Threshold uncertainty score0.386

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.018
GPT teacher head0.247
Teacher spread0.228 · 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